1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc/private/kernels/blocktranspose.h> 12 13 PetscErrorCode MatSeqAIJSetTypeFromOptions(Mat A) 14 { 15 PetscErrorCode ierr; 16 PetscBool flg; 17 char type[256]; 18 19 PetscFunctionBegin; 20 ierr = PetscObjectOptionsBegin((PetscObject)A); 21 ierr = PetscOptionsFList("-mat_seqaij_type","Matrix SeqAIJ type","MatSeqAIJSetType",MatSeqAIJList,"seqaij",type,256,&flg);CHKERRQ(ierr); 22 if (flg) { 23 ierr = MatSeqAIJSetType(A,type);CHKERRQ(ierr); 24 } 25 ierr = PetscOptionsEnd();CHKERRQ(ierr); 26 PetscFunctionReturn(0); 27 } 28 29 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 30 { 31 PetscErrorCode ierr; 32 PetscInt i,m,n; 33 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 34 35 PetscFunctionBegin; 36 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 37 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 38 if (type == NORM_2) { 39 for (i=0; i<aij->i[m]; i++) { 40 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 41 } 42 } else if (type == NORM_1) { 43 for (i=0; i<aij->i[m]; i++) { 44 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 45 } 46 } else if (type == NORM_INFINITY) { 47 for (i=0; i<aij->i[m]; i++) { 48 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 49 } 50 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 51 52 if (type == NORM_2) { 53 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 54 } 55 PetscFunctionReturn(0); 56 } 57 58 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 59 { 60 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 61 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 62 const PetscInt *jj = a->j,*ii = a->i; 63 PetscInt *rows; 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 for (i=0; i<m; i++) { 68 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 69 cnt++; 70 } 71 } 72 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 73 cnt = 0; 74 for (i=0; i<m; i++) { 75 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 76 rows[cnt] = i; 77 cnt++; 78 } 79 } 80 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 81 PetscFunctionReturn(0); 82 } 83 84 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 85 { 86 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 87 const MatScalar *aa = a->a; 88 PetscInt i,m=A->rmap->n,cnt = 0; 89 const PetscInt *ii = a->i,*jj = a->j,*diag; 90 PetscInt *rows; 91 PetscErrorCode ierr; 92 93 PetscFunctionBegin; 94 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 95 diag = a->diag; 96 for (i=0; i<m; i++) { 97 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 98 cnt++; 99 } 100 } 101 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 102 cnt = 0; 103 for (i=0; i<m; i++) { 104 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 105 rows[cnt++] = i; 106 } 107 } 108 *nrows = cnt; 109 *zrows = rows; 110 PetscFunctionReturn(0); 111 } 112 113 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 114 { 115 PetscInt nrows,*rows; 116 PetscErrorCode ierr; 117 118 PetscFunctionBegin; 119 *zrows = NULL; 120 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 121 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 122 PetscFunctionReturn(0); 123 } 124 125 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 126 { 127 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 128 const MatScalar *aa; 129 PetscInt m=A->rmap->n,cnt = 0; 130 const PetscInt *ii; 131 PetscInt n,i,j,*rows; 132 PetscErrorCode ierr; 133 134 PetscFunctionBegin; 135 *keptrows = 0; 136 ii = a->i; 137 for (i=0; i<m; i++) { 138 n = ii[i+1] - ii[i]; 139 if (!n) { 140 cnt++; 141 goto ok1; 142 } 143 aa = a->a + ii[i]; 144 for (j=0; j<n; j++) { 145 if (aa[j] != 0.0) goto ok1; 146 } 147 cnt++; 148 ok1:; 149 } 150 if (!cnt) PetscFunctionReturn(0); 151 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 152 cnt = 0; 153 for (i=0; i<m; i++) { 154 n = ii[i+1] - ii[i]; 155 if (!n) continue; 156 aa = a->a + ii[i]; 157 for (j=0; j<n; j++) { 158 if (aa[j] != 0.0) { 159 rows[cnt++] = i; 160 break; 161 } 162 } 163 } 164 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 165 PetscFunctionReturn(0); 166 } 167 168 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 169 { 170 PetscErrorCode ierr; 171 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 172 PetscInt i,m = Y->rmap->n; 173 const PetscInt *diag; 174 MatScalar *aa = aij->a; 175 const PetscScalar *v; 176 PetscBool missing; 177 178 PetscFunctionBegin; 179 if (Y->assembled) { 180 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 181 if (!missing) { 182 diag = aij->diag; 183 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 184 if (is == INSERT_VALUES) { 185 for (i=0; i<m; i++) { 186 aa[diag[i]] = v[i]; 187 } 188 } else { 189 for (i=0; i<m; i++) { 190 aa[diag[i]] += v[i]; 191 } 192 } 193 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 194 PetscFunctionReturn(0); 195 } 196 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 197 } 198 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 199 PetscFunctionReturn(0); 200 } 201 202 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 203 { 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 PetscErrorCode ierr; 206 PetscInt i,ishift; 207 208 PetscFunctionBegin; 209 *m = A->rmap->n; 210 if (!ia) PetscFunctionReturn(0); 211 ishift = 0; 212 if (symmetric && !A->structurally_symmetric) { 213 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 214 } else if (oshift == 1) { 215 PetscInt *tia; 216 PetscInt nz = a->i[A->rmap->n]; 217 /* malloc space and add 1 to i and j indices */ 218 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 219 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 220 *ia = tia; 221 if (ja) { 222 PetscInt *tja; 223 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 224 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 225 *ja = tja; 226 } 227 } else { 228 *ia = a->i; 229 if (ja) *ja = a->j; 230 } 231 PetscFunctionReturn(0); 232 } 233 234 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 235 { 236 PetscErrorCode ierr; 237 238 PetscFunctionBegin; 239 if (!ia) PetscFunctionReturn(0); 240 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 241 ierr = PetscFree(*ia);CHKERRQ(ierr); 242 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 243 } 244 PetscFunctionReturn(0); 245 } 246 247 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 248 { 249 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 250 PetscErrorCode ierr; 251 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 252 PetscInt nz = a->i[m],row,*jj,mr,col; 253 254 PetscFunctionBegin; 255 *nn = n; 256 if (!ia) PetscFunctionReturn(0); 257 if (symmetric) { 258 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 259 } else { 260 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 261 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 262 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 263 jj = a->j; 264 for (i=0; i<nz; i++) { 265 collengths[jj[i]]++; 266 } 267 cia[0] = oshift; 268 for (i=0; i<n; i++) { 269 cia[i+1] = cia[i] + collengths[i]; 270 } 271 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 272 jj = a->j; 273 for (row=0; row<m; row++) { 274 mr = a->i[row+1] - a->i[row]; 275 for (i=0; i<mr; i++) { 276 col = *jj++; 277 278 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 279 } 280 } 281 ierr = PetscFree(collengths);CHKERRQ(ierr); 282 *ia = cia; *ja = cja; 283 } 284 PetscFunctionReturn(0); 285 } 286 287 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 288 { 289 PetscErrorCode ierr; 290 291 PetscFunctionBegin; 292 if (!ia) PetscFunctionReturn(0); 293 294 ierr = PetscFree(*ia);CHKERRQ(ierr); 295 ierr = PetscFree(*ja);CHKERRQ(ierr); 296 PetscFunctionReturn(0); 297 } 298 299 /* 300 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 301 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 302 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 303 */ 304 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 305 { 306 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 307 PetscErrorCode ierr; 308 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 309 PetscInt nz = a->i[m],row,*jj,mr,col; 310 PetscInt *cspidx; 311 312 PetscFunctionBegin; 313 *nn = n; 314 if (!ia) PetscFunctionReturn(0); 315 316 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 317 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 318 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 319 ierr = PetscMalloc1(nz+1,&cspidx);CHKERRQ(ierr); 320 jj = a->j; 321 for (i=0; i<nz; i++) { 322 collengths[jj[i]]++; 323 } 324 cia[0] = oshift; 325 for (i=0; i<n; i++) { 326 cia[i+1] = cia[i] + collengths[i]; 327 } 328 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 329 jj = a->j; 330 for (row=0; row<m; row++) { 331 mr = a->i[row+1] - a->i[row]; 332 for (i=0; i<mr; i++) { 333 col = *jj++; 334 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 335 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 336 } 337 } 338 ierr = PetscFree(collengths);CHKERRQ(ierr); 339 *ia = cia; *ja = cja; 340 *spidx = cspidx; 341 PetscFunctionReturn(0); 342 } 343 344 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 345 { 346 PetscErrorCode ierr; 347 348 PetscFunctionBegin; 349 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 350 ierr = PetscFree(*spidx);CHKERRQ(ierr); 351 PetscFunctionReturn(0); 352 } 353 354 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 355 { 356 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 357 PetscInt *ai = a->i; 358 PetscErrorCode ierr; 359 360 PetscFunctionBegin; 361 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 362 PetscFunctionReturn(0); 363 } 364 365 /* 366 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 367 368 - a single row of values is set with each call 369 - no row or column indices are negative or (in error) larger than the number of rows or columns 370 - the values are always added to the matrix, not set 371 - no new locations are introduced in the nonzero structure of the matrix 372 373 This does NOT assume the global column indices are sorted 374 375 */ 376 377 #include <petsc/private/isimpl.h> 378 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 379 { 380 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 381 PetscInt low,high,t,row,nrow,i,col,l; 382 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 383 PetscInt lastcol = -1; 384 MatScalar *ap,value,*aa = a->a; 385 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 386 387 row = ridx[im[0]]; 388 rp = aj + ai[row]; 389 ap = aa + ai[row]; 390 nrow = ailen[row]; 391 low = 0; 392 high = nrow; 393 for (l=0; l<n; l++) { /* loop over added columns */ 394 col = cidx[in[l]]; 395 value = v[l]; 396 397 if (col <= lastcol) low = 0; 398 else high = nrow; 399 lastcol = col; 400 while (high-low > 5) { 401 t = (low+high)/2; 402 if (rp[t] > col) high = t; 403 else low = t; 404 } 405 for (i=low; i<high; i++) { 406 if (rp[i] == col) { 407 ap[i] += value; 408 low = i + 1; 409 break; 410 } 411 } 412 } 413 return 0; 414 } 415 416 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 417 { 418 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 419 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 420 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 421 PetscErrorCode ierr; 422 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 423 MatScalar *ap=NULL,value=0.0,*aa = a->a; 424 PetscBool ignorezeroentries = a->ignorezeroentries; 425 PetscBool roworiented = a->roworiented; 426 427 PetscFunctionBegin; 428 for (k=0; k<m; k++) { /* loop over added rows */ 429 row = im[k]; 430 if (row < 0) continue; 431 #if defined(PETSC_USE_DEBUG) 432 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 433 #endif 434 rp = aj + ai[row]; 435 if (!A->structure_only) ap = aa + ai[row]; 436 rmax = imax[row]; nrow = ailen[row]; 437 low = 0; 438 high = nrow; 439 for (l=0; l<n; l++) { /* loop over added columns */ 440 if (in[l] < 0) continue; 441 #if defined(PETSC_USE_DEBUG) 442 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 443 #endif 444 col = in[l]; 445 if (!A->structure_only) { 446 if (roworiented) { 447 value = v[l + k*n]; 448 } else { 449 value = v[k + l*m]; 450 } 451 } else { /* A->structure_only */ 452 value = 1; /* avoid 'continue' below? */ 453 } 454 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES) && row != col) continue; 455 456 if (col <= lastcol) low = 0; 457 else high = nrow; 458 lastcol = col; 459 while (high-low > 5) { 460 t = (low+high)/2; 461 if (rp[t] > col) high = t; 462 else low = t; 463 } 464 for (i=low; i<high; i++) { 465 if (rp[i] > col) break; 466 if (rp[i] == col) { 467 if (!A->structure_only) { 468 if (is == ADD_VALUES) ap[i] += value; 469 else ap[i] = value; 470 } 471 low = i + 1; 472 goto noinsert; 473 } 474 } 475 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 476 if (nonew == 1) goto noinsert; 477 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 478 if (A->structure_only) { 479 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 480 } else { 481 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 482 } 483 N = nrow++ - 1; a->nz++; high++; 484 /* shift up all the later entries in this row */ 485 for (ii=N; ii>=i; ii--) { 486 rp[ii+1] = rp[ii]; 487 if (!A->structure_only) ap[ii+1] = ap[ii]; 488 } 489 rp[i] = col; 490 if (!A->structure_only) ap[i] = value; 491 low = i + 1; 492 A->nonzerostate++; 493 noinsert:; 494 } 495 ailen[row] = nrow; 496 } 497 PetscFunctionReturn(0); 498 } 499 500 501 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 502 { 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 504 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 505 PetscInt *ai = a->i,*ailen = a->ilen; 506 MatScalar *ap,*aa = a->a; 507 508 PetscFunctionBegin; 509 for (k=0; k<m; k++) { /* loop over rows */ 510 row = im[k]; 511 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 512 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 513 rp = aj + ai[row]; ap = aa + ai[row]; 514 nrow = ailen[row]; 515 for (l=0; l<n; l++) { /* loop over columns */ 516 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 517 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 518 col = in[l]; 519 high = nrow; low = 0; /* assume unsorted */ 520 while (high-low > 5) { 521 t = (low+high)/2; 522 if (rp[t] > col) high = t; 523 else low = t; 524 } 525 for (i=low; i<high; i++) { 526 if (rp[i] > col) break; 527 if (rp[i] == col) { 528 *v++ = ap[i]; 529 goto finished; 530 } 531 } 532 *v++ = 0.0; 533 finished:; 534 } 535 } 536 PetscFunctionReturn(0); 537 } 538 539 540 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 541 { 542 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 543 PetscErrorCode ierr; 544 PetscInt i,*col_lens; 545 int fd; 546 FILE *file; 547 548 PetscFunctionBegin; 549 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 550 ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); 551 552 col_lens[0] = MAT_FILE_CLASSID; 553 col_lens[1] = A->rmap->n; 554 col_lens[2] = A->cmap->n; 555 col_lens[3] = a->nz; 556 557 /* store lengths of each row and write (including header) to file */ 558 for (i=0; i<A->rmap->n; i++) { 559 col_lens[4+i] = a->i[i+1] - a->i[i]; 560 } 561 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 562 ierr = PetscFree(col_lens);CHKERRQ(ierr); 563 564 /* store column indices (zero start index) */ 565 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 566 567 /* store nonzero values */ 568 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 569 570 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 571 if (file) { 572 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 573 } 574 PetscFunctionReturn(0); 575 } 576 577 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 578 { 579 PetscErrorCode ierr; 580 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 581 PetscInt i,k,m=A->rmap->N; 582 583 PetscFunctionBegin; 584 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 585 for (i=0; i<m; i++) { 586 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 587 for (k=a->i[i]; k<a->i[i+1]; k++) { 588 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 589 } 590 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 591 } 592 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 593 PetscFunctionReturn(0); 594 } 595 596 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 597 598 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 599 { 600 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 601 PetscErrorCode ierr; 602 PetscInt i,j,m = A->rmap->n; 603 const char *name; 604 PetscViewerFormat format; 605 606 PetscFunctionBegin; 607 if (A->structure_only) { 608 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 609 PetscFunctionReturn(0); 610 } 611 612 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 613 if (format == PETSC_VIEWER_ASCII_MATLAB) { 614 PetscInt nofinalvalue = 0; 615 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 616 /* Need a dummy value to ensure the dimension of the matrix. */ 617 nofinalvalue = 1; 618 } 619 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 620 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 621 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 622 #if defined(PETSC_USE_COMPLEX) 623 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 624 #else 625 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 626 #endif 627 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 628 629 for (i=0; i<m; i++) { 630 for (j=a->i[i]; j<a->i[i+1]; j++) { 631 #if defined(PETSC_USE_COMPLEX) 632 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",i+1,a->j[j]+1,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 633 #else 634 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 635 #endif 636 } 637 } 638 if (nofinalvalue) { 639 #if defined(PETSC_USE_COMPLEX) 640 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 641 #else 642 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 643 #endif 644 } 645 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 646 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 647 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 648 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 649 PetscFunctionReturn(0); 650 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 651 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 652 for (i=0; i<m; i++) { 653 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 654 for (j=a->i[i]; j<a->i[i+1]; j++) { 655 #if defined(PETSC_USE_COMPLEX) 656 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 657 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 658 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 659 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 660 } else if (PetscRealPart(a->a[j]) != 0.0) { 661 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 662 } 663 #else 664 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 665 #endif 666 } 667 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 668 } 669 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 670 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 671 PetscInt nzd=0,fshift=1,*sptr; 672 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 674 for (i=0; i<m; i++) { 675 sptr[i] = nzd+1; 676 for (j=a->i[i]; j<a->i[i+1]; j++) { 677 if (a->j[j] >= i) { 678 #if defined(PETSC_USE_COMPLEX) 679 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 680 #else 681 if (a->a[j] != 0.0) nzd++; 682 #endif 683 } 684 } 685 } 686 sptr[m] = nzd+1; 687 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 688 for (i=0; i<m+1; i+=6) { 689 if (i+4<m) { 690 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]);CHKERRQ(ierr); 691 } else if (i+3<m) { 692 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]);CHKERRQ(ierr); 693 } else if (i+2<m) { 694 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 695 } else if (i+1<m) { 696 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 697 } else if (i<m) { 698 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 699 } else { 700 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 701 } 702 } 703 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 704 ierr = PetscFree(sptr);CHKERRQ(ierr); 705 for (i=0; i<m; i++) { 706 for (j=a->i[i]; j<a->i[i+1]; j++) { 707 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 708 } 709 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 710 } 711 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 712 for (i=0; i<m; i++) { 713 for (j=a->i[i]; j<a->i[i+1]; j++) { 714 if (a->j[j] >= i) { 715 #if defined(PETSC_USE_COMPLEX) 716 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 717 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 718 } 719 #else 720 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 721 #endif 722 } 723 } 724 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 725 } 726 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 727 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 728 PetscInt cnt = 0,jcnt; 729 PetscScalar value; 730 #if defined(PETSC_USE_COMPLEX) 731 PetscBool realonly = PETSC_TRUE; 732 733 for (i=0; i<a->i[m]; i++) { 734 if (PetscImaginaryPart(a->a[i]) != 0.0) { 735 realonly = PETSC_FALSE; 736 break; 737 } 738 } 739 #endif 740 741 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 742 for (i=0; i<m; i++) { 743 jcnt = 0; 744 for (j=0; j<A->cmap->n; j++) { 745 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 746 value = a->a[cnt++]; 747 jcnt++; 748 } else { 749 value = 0.0; 750 } 751 #if defined(PETSC_USE_COMPLEX) 752 if (realonly) { 753 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 754 } else { 755 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 756 } 757 #else 758 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 759 #endif 760 } 761 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 762 } 763 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 764 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 765 PetscInt fshift=1; 766 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 767 #if defined(PETSC_USE_COMPLEX) 768 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 769 #else 770 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 771 #endif 772 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 773 for (i=0; i<m; i++) { 774 for (j=a->i[i]; j<a->i[i+1]; j++) { 775 #if defined(PETSC_USE_COMPLEX) 776 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 777 #else 778 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 779 #endif 780 } 781 } 782 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 783 } else { 784 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 785 if (A->factortype) { 786 for (i=0; i<m; i++) { 787 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 788 /* L part */ 789 for (j=a->i[i]; j<a->i[i+1]; j++) { 790 #if defined(PETSC_USE_COMPLEX) 791 if (PetscImaginaryPart(a->a[j]) > 0.0) { 792 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 793 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 794 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 795 } else { 796 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 797 } 798 #else 799 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 800 #endif 801 } 802 /* diagonal */ 803 j = a->diag[i]; 804 #if defined(PETSC_USE_COMPLEX) 805 if (PetscImaginaryPart(a->a[j]) > 0.0) { 806 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 807 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 808 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 809 } else { 810 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 811 } 812 #else 813 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 814 #endif 815 816 /* U part */ 817 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 818 #if defined(PETSC_USE_COMPLEX) 819 if (PetscImaginaryPart(a->a[j]) > 0.0) { 820 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 821 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 822 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 823 } else { 824 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 825 } 826 #else 827 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 828 #endif 829 } 830 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 831 } 832 } else { 833 for (i=0; i<m; i++) { 834 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 835 for (j=a->i[i]; j<a->i[i+1]; j++) { 836 #if defined(PETSC_USE_COMPLEX) 837 if (PetscImaginaryPart(a->a[j]) > 0.0) { 838 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 839 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 840 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 841 } else { 842 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 843 } 844 #else 845 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 846 #endif 847 } 848 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 849 } 850 } 851 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 852 } 853 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 854 PetscFunctionReturn(0); 855 } 856 857 #include <petscdraw.h> 858 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 859 { 860 Mat A = (Mat) Aa; 861 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 862 PetscErrorCode ierr; 863 PetscInt i,j,m = A->rmap->n; 864 int color; 865 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 866 PetscViewer viewer; 867 PetscViewerFormat format; 868 869 PetscFunctionBegin; 870 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 871 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 872 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 873 874 /* loop over matrix elements drawing boxes */ 875 876 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 877 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 878 /* Blue for negative, Cyan for zero and Red for positive */ 879 color = PETSC_DRAW_BLUE; 880 for (i=0; i<m; i++) { 881 y_l = m - i - 1.0; y_r = y_l + 1.0; 882 for (j=a->i[i]; j<a->i[i+1]; j++) { 883 x_l = a->j[j]; x_r = x_l + 1.0; 884 if (PetscRealPart(a->a[j]) >= 0.) continue; 885 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 886 } 887 } 888 color = PETSC_DRAW_CYAN; 889 for (i=0; i<m; i++) { 890 y_l = m - i - 1.0; y_r = y_l + 1.0; 891 for (j=a->i[i]; j<a->i[i+1]; j++) { 892 x_l = a->j[j]; x_r = x_l + 1.0; 893 if (a->a[j] != 0.) continue; 894 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 895 } 896 } 897 color = PETSC_DRAW_RED; 898 for (i=0; i<m; i++) { 899 y_l = m - i - 1.0; y_r = y_l + 1.0; 900 for (j=a->i[i]; j<a->i[i+1]; j++) { 901 x_l = a->j[j]; x_r = x_l + 1.0; 902 if (PetscRealPart(a->a[j]) <= 0.) continue; 903 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 904 } 905 } 906 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 907 } else { 908 /* use contour shading to indicate magnitude of values */ 909 /* first determine max of all nonzero values */ 910 PetscReal minv = 0.0, maxv = 0.0; 911 PetscInt nz = a->nz, count = 0; 912 PetscDraw popup; 913 914 for (i=0; i<nz; i++) { 915 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 916 } 917 if (minv >= maxv) maxv = minv + PETSC_SMALL; 918 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 919 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 920 921 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 922 for (i=0; i<m; i++) { 923 y_l = m - i - 1.0; 924 y_r = y_l + 1.0; 925 for (j=a->i[i]; j<a->i[i+1]; j++) { 926 x_l = a->j[j]; 927 x_r = x_l + 1.0; 928 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 929 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 930 count++; 931 } 932 } 933 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 934 } 935 PetscFunctionReturn(0); 936 } 937 938 #include <petscdraw.h> 939 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 940 { 941 PetscErrorCode ierr; 942 PetscDraw draw; 943 PetscReal xr,yr,xl,yl,h,w; 944 PetscBool isnull; 945 946 PetscFunctionBegin; 947 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 948 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 949 if (isnull) PetscFunctionReturn(0); 950 951 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 952 xr += w; yr += h; xl = -w; yl = -h; 953 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 954 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 955 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 956 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 957 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 962 { 963 PetscErrorCode ierr; 964 PetscBool iascii,isbinary,isdraw; 965 966 PetscFunctionBegin; 967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 968 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 969 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 970 if (iascii) { 971 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 972 } else if (isbinary) { 973 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 974 } else if (isdraw) { 975 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 976 } 977 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 978 PetscFunctionReturn(0); 979 } 980 981 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 982 { 983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 984 PetscErrorCode ierr; 985 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 986 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 987 MatScalar *aa = a->a,*ap; 988 PetscReal ratio = 0.6; 989 990 PetscFunctionBegin; 991 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 992 993 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 994 for (i=1; i<m; i++) { 995 /* move each row back by the amount of empty slots (fshift) before it*/ 996 fshift += imax[i-1] - ailen[i-1]; 997 rmax = PetscMax(rmax,ailen[i]); 998 if (fshift) { 999 ip = aj + ai[i]; 1000 ap = aa + ai[i]; 1001 N = ailen[i]; 1002 for (j=0; j<N; j++) { 1003 ip[j-fshift] = ip[j]; 1004 if (!A->structure_only) ap[j-fshift] = ap[j]; 1005 } 1006 } 1007 ai[i] = ai[i-1] + ailen[i-1]; 1008 } 1009 if (m) { 1010 fshift += imax[m-1] - ailen[m-1]; 1011 ai[m] = ai[m-1] + ailen[m-1]; 1012 } 1013 1014 /* reset ilen and imax for each row */ 1015 a->nonzerorowcnt = 0; 1016 if (A->structure_only) { 1017 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1018 } else { /* !A->structure_only */ 1019 for (i=0; i<m; i++) { 1020 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1021 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1022 } 1023 } 1024 a->nz = ai[m]; 1025 if (fshift && a->nounused == -1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D, %D unneeded", m, A->cmap->n, fshift); 1026 1027 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1028 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1029 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1030 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1031 1032 A->info.mallocs += a->reallocs; 1033 a->reallocs = 0; 1034 A->info.nz_unneeded = (PetscReal)fshift; 1035 a->rmax = rmax; 1036 1037 if (!A->structure_only) { 1038 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1039 } 1040 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1041 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1042 PetscFunctionReturn(0); 1043 } 1044 1045 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1046 { 1047 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1048 PetscInt i,nz = a->nz; 1049 MatScalar *aa = a->a; 1050 PetscErrorCode ierr; 1051 1052 PetscFunctionBegin; 1053 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1054 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1059 { 1060 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1061 PetscInt i,nz = a->nz; 1062 MatScalar *aa = a->a; 1063 PetscErrorCode ierr; 1064 1065 PetscFunctionBegin; 1066 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1067 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1068 PetscFunctionReturn(0); 1069 } 1070 1071 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1072 { 1073 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1078 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1083 { 1084 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1085 PetscErrorCode ierr; 1086 1087 PetscFunctionBegin; 1088 #if defined(PETSC_USE_LOG) 1089 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1090 #endif 1091 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1092 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1093 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1094 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1095 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1096 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1097 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1098 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1099 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1100 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1101 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1102 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1103 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1104 1105 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1106 ierr = PetscFree(A->data);CHKERRQ(ierr); 1107 1108 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1109 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1110 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1115 #if defined(PETSC_HAVE_ELEMENTAL) 1116 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1117 #endif 1118 #if defined(PETSC_HAVE_HYPRE) 1119 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1120 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1121 #endif 1122 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1123 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1124 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1131 { 1132 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1133 PetscErrorCode ierr; 1134 1135 PetscFunctionBegin; 1136 switch (op) { 1137 case MAT_ROW_ORIENTED: 1138 a->roworiented = flg; 1139 break; 1140 case MAT_KEEP_NONZERO_PATTERN: 1141 a->keepnonzeropattern = flg; 1142 break; 1143 case MAT_NEW_NONZERO_LOCATIONS: 1144 a->nonew = (flg ? 0 : 1); 1145 break; 1146 case MAT_NEW_NONZERO_LOCATION_ERR: 1147 a->nonew = (flg ? -1 : 0); 1148 break; 1149 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1150 a->nonew = (flg ? -2 : 0); 1151 break; 1152 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1153 a->nounused = (flg ? -1 : 0); 1154 break; 1155 case MAT_IGNORE_ZERO_ENTRIES: 1156 a->ignorezeroentries = flg; 1157 break; 1158 case MAT_SPD: 1159 case MAT_SYMMETRIC: 1160 case MAT_STRUCTURALLY_SYMMETRIC: 1161 case MAT_HERMITIAN: 1162 case MAT_SYMMETRY_ETERNAL: 1163 case MAT_STRUCTURE_ONLY: 1164 /* These options are handled directly by MatSetOption() */ 1165 break; 1166 case MAT_NEW_DIAGONALS: 1167 case MAT_IGNORE_OFF_PROC_ENTRIES: 1168 case MAT_USE_HASH_TABLE: 1169 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1170 break; 1171 case MAT_USE_INODES: 1172 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1173 break; 1174 case MAT_SUBMAT_SINGLEIS: 1175 A->submat_singleis = flg; 1176 break; 1177 default: 1178 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1179 } 1180 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1181 PetscFunctionReturn(0); 1182 } 1183 1184 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1185 { 1186 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1187 PetscErrorCode ierr; 1188 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1189 PetscScalar *aa=a->a,*x,zero=0.0; 1190 1191 PetscFunctionBegin; 1192 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1193 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1194 1195 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1196 PetscInt *diag=a->diag; 1197 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1198 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1199 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1200 PetscFunctionReturn(0); 1201 } 1202 1203 ierr = VecSet(v,zero);CHKERRQ(ierr); 1204 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1205 for (i=0; i<n; i++) { 1206 nz = ai[i+1] - ai[i]; 1207 if (!nz) x[i] = 0.0; 1208 for (j=ai[i]; j<ai[i+1]; j++) { 1209 if (aj[j] == i) { 1210 x[i] = aa[j]; 1211 break; 1212 } 1213 } 1214 } 1215 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1220 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1221 { 1222 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1223 PetscScalar *y; 1224 const PetscScalar *x; 1225 PetscErrorCode ierr; 1226 PetscInt m = A->rmap->n; 1227 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1228 const MatScalar *v; 1229 PetscScalar alpha; 1230 PetscInt n,i,j; 1231 const PetscInt *idx,*ii,*ridx=NULL; 1232 Mat_CompressedRow cprow = a->compressedrow; 1233 PetscBool usecprow = cprow.use; 1234 #endif 1235 1236 PetscFunctionBegin; 1237 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1238 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1239 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1240 1241 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1242 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1243 #else 1244 if (usecprow) { 1245 m = cprow.nrows; 1246 ii = cprow.i; 1247 ridx = cprow.rindex; 1248 } else { 1249 ii = a->i; 1250 } 1251 for (i=0; i<m; i++) { 1252 idx = a->j + ii[i]; 1253 v = a->a + ii[i]; 1254 n = ii[i+1] - ii[i]; 1255 if (usecprow) { 1256 alpha = x[ridx[i]]; 1257 } else { 1258 alpha = x[i]; 1259 } 1260 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1261 } 1262 #endif 1263 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1264 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1265 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1266 PetscFunctionReturn(0); 1267 } 1268 1269 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1270 { 1271 PetscErrorCode ierr; 1272 1273 PetscFunctionBegin; 1274 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1275 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1276 PetscFunctionReturn(0); 1277 } 1278 1279 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1280 1281 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1282 { 1283 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1284 PetscScalar *y; 1285 const PetscScalar *x; 1286 const MatScalar *aa; 1287 PetscErrorCode ierr; 1288 PetscInt m=A->rmap->n; 1289 const PetscInt *aj,*ii,*ridx=NULL; 1290 PetscInt n,i; 1291 PetscScalar sum; 1292 PetscBool usecprow=a->compressedrow.use; 1293 1294 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1295 #pragma disjoint(*x,*y,*aa) 1296 #endif 1297 1298 PetscFunctionBegin; 1299 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1300 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1301 ii = a->i; 1302 if (usecprow) { /* use compressed row format */ 1303 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1304 m = a->compressedrow.nrows; 1305 ii = a->compressedrow.i; 1306 ridx = a->compressedrow.rindex; 1307 for (i=0; i<m; i++) { 1308 n = ii[i+1] - ii[i]; 1309 aj = a->j + ii[i]; 1310 aa = a->a + ii[i]; 1311 sum = 0.0; 1312 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1313 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1314 y[*ridx++] = sum; 1315 } 1316 } else { /* do not use compressed row format */ 1317 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1318 aj = a->j; 1319 aa = a->a; 1320 fortranmultaij_(&m,x,ii,aj,aa,y); 1321 #else 1322 for (i=0; i<m; i++) { 1323 n = ii[i+1] - ii[i]; 1324 aj = a->j + ii[i]; 1325 aa = a->a + ii[i]; 1326 sum = 0.0; 1327 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1328 y[i] = sum; 1329 } 1330 #endif 1331 } 1332 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1333 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1334 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1335 PetscFunctionReturn(0); 1336 } 1337 1338 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1339 { 1340 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1341 PetscScalar *y; 1342 const PetscScalar *x; 1343 const MatScalar *aa; 1344 PetscErrorCode ierr; 1345 PetscInt m=A->rmap->n; 1346 const PetscInt *aj,*ii,*ridx=NULL; 1347 PetscInt n,i,nonzerorow=0; 1348 PetscScalar sum; 1349 PetscBool usecprow=a->compressedrow.use; 1350 1351 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1352 #pragma disjoint(*x,*y,*aa) 1353 #endif 1354 1355 PetscFunctionBegin; 1356 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1357 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1358 if (usecprow) { /* use compressed row format */ 1359 m = a->compressedrow.nrows; 1360 ii = a->compressedrow.i; 1361 ridx = a->compressedrow.rindex; 1362 for (i=0; i<m; i++) { 1363 n = ii[i+1] - ii[i]; 1364 aj = a->j + ii[i]; 1365 aa = a->a + ii[i]; 1366 sum = 0.0; 1367 nonzerorow += (n>0); 1368 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1369 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1370 y[*ridx++] = sum; 1371 } 1372 } else { /* do not use compressed row format */ 1373 ii = a->i; 1374 for (i=0; i<m; i++) { 1375 n = ii[i+1] - ii[i]; 1376 aj = a->j + ii[i]; 1377 aa = a->a + ii[i]; 1378 sum = 0.0; 1379 nonzerorow += (n>0); 1380 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1381 y[i] = sum; 1382 } 1383 } 1384 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1385 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1386 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1387 PetscFunctionReturn(0); 1388 } 1389 1390 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1391 { 1392 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1393 PetscScalar *y,*z; 1394 const PetscScalar *x; 1395 const MatScalar *aa; 1396 PetscErrorCode ierr; 1397 PetscInt m = A->rmap->n,*aj,*ii; 1398 PetscInt n,i,*ridx=NULL; 1399 PetscScalar sum; 1400 PetscBool usecprow=a->compressedrow.use; 1401 1402 PetscFunctionBegin; 1403 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1404 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1405 if (usecprow) { /* use compressed row format */ 1406 if (zz != yy) { 1407 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1408 } 1409 m = a->compressedrow.nrows; 1410 ii = a->compressedrow.i; 1411 ridx = a->compressedrow.rindex; 1412 for (i=0; i<m; i++) { 1413 n = ii[i+1] - ii[i]; 1414 aj = a->j + ii[i]; 1415 aa = a->a + ii[i]; 1416 sum = y[*ridx]; 1417 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1418 z[*ridx++] = sum; 1419 } 1420 } else { /* do not use compressed row format */ 1421 ii = a->i; 1422 for (i=0; i<m; i++) { 1423 n = ii[i+1] - ii[i]; 1424 aj = a->j + ii[i]; 1425 aa = a->a + ii[i]; 1426 sum = y[i]; 1427 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1428 z[i] = sum; 1429 } 1430 } 1431 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1432 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1433 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1434 PetscFunctionReturn(0); 1435 } 1436 1437 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1438 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1439 { 1440 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1441 PetscScalar *y,*z; 1442 const PetscScalar *x; 1443 const MatScalar *aa; 1444 PetscErrorCode ierr; 1445 const PetscInt *aj,*ii,*ridx=NULL; 1446 PetscInt m = A->rmap->n,n,i; 1447 PetscScalar sum; 1448 PetscBool usecprow=a->compressedrow.use; 1449 1450 PetscFunctionBegin; 1451 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1452 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1453 if (usecprow) { /* use compressed row format */ 1454 if (zz != yy) { 1455 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1456 } 1457 m = a->compressedrow.nrows; 1458 ii = a->compressedrow.i; 1459 ridx = a->compressedrow.rindex; 1460 for (i=0; i<m; i++) { 1461 n = ii[i+1] - ii[i]; 1462 aj = a->j + ii[i]; 1463 aa = a->a + ii[i]; 1464 sum = y[*ridx]; 1465 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1466 z[*ridx++] = sum; 1467 } 1468 } else { /* do not use compressed row format */ 1469 ii = a->i; 1470 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1471 aj = a->j; 1472 aa = a->a; 1473 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1474 #else 1475 for (i=0; i<m; i++) { 1476 n = ii[i+1] - ii[i]; 1477 aj = a->j + ii[i]; 1478 aa = a->a + ii[i]; 1479 sum = y[i]; 1480 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1481 z[i] = sum; 1482 } 1483 #endif 1484 } 1485 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1486 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1487 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1488 #if defined(PETSC_HAVE_CUSP) 1489 /* 1490 ierr = VecView(xx,0);CHKERRQ(ierr); 1491 ierr = VecView(zz,0);CHKERRQ(ierr); 1492 ierr = MatView(A,0);CHKERRQ(ierr); 1493 */ 1494 #endif 1495 PetscFunctionReturn(0); 1496 } 1497 1498 /* 1499 Adds diagonal pointers to sparse matrix structure. 1500 */ 1501 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1502 { 1503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1504 PetscErrorCode ierr; 1505 PetscInt i,j,m = A->rmap->n; 1506 1507 PetscFunctionBegin; 1508 if (!a->diag) { 1509 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1510 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1511 } 1512 for (i=0; i<A->rmap->n; i++) { 1513 a->diag[i] = a->i[i+1]; 1514 for (j=a->i[i]; j<a->i[i+1]; j++) { 1515 if (a->j[j] == i) { 1516 a->diag[i] = j; 1517 break; 1518 } 1519 } 1520 } 1521 PetscFunctionReturn(0); 1522 } 1523 1524 /* 1525 Checks for missing diagonals 1526 */ 1527 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1528 { 1529 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1530 PetscInt *diag,*ii = a->i,i; 1531 1532 PetscFunctionBegin; 1533 *missing = PETSC_FALSE; 1534 if (A->rmap->n > 0 && !ii) { 1535 *missing = PETSC_TRUE; 1536 if (d) *d = 0; 1537 PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); 1538 } else { 1539 diag = a->diag; 1540 for (i=0; i<A->rmap->n; i++) { 1541 if (diag[i] >= ii[i+1]) { 1542 *missing = PETSC_TRUE; 1543 if (d) *d = i; 1544 PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); 1545 break; 1546 } 1547 } 1548 } 1549 PetscFunctionReturn(0); 1550 } 1551 1552 /* 1553 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1554 */ 1555 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1556 { 1557 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1558 PetscErrorCode ierr; 1559 PetscInt i,*diag,m = A->rmap->n; 1560 MatScalar *v = a->a; 1561 PetscScalar *idiag,*mdiag; 1562 1563 PetscFunctionBegin; 1564 if (a->idiagvalid) PetscFunctionReturn(0); 1565 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1566 diag = a->diag; 1567 if (!a->idiag) { 1568 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1569 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1570 v = a->a; 1571 } 1572 mdiag = a->mdiag; 1573 idiag = a->idiag; 1574 1575 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1576 for (i=0; i<m; i++) { 1577 mdiag[i] = v[diag[i]]; 1578 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1579 if (PetscRealPart(fshift)) { 1580 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1581 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1582 A->factorerror_zeropivot_value = 0.0; 1583 A->factorerror_zeropivot_row = i; 1584 } SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1585 } 1586 idiag[i] = 1.0/v[diag[i]]; 1587 } 1588 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1589 } else { 1590 for (i=0; i<m; i++) { 1591 mdiag[i] = v[diag[i]]; 1592 idiag[i] = omega/(fshift + v[diag[i]]); 1593 } 1594 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1595 } 1596 a->idiagvalid = PETSC_TRUE; 1597 PetscFunctionReturn(0); 1598 } 1599 1600 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1601 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1602 { 1603 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1604 PetscScalar *x,d,sum,*t,scale; 1605 const MatScalar *v,*idiag=0,*mdiag; 1606 const PetscScalar *b, *bs,*xb, *ts; 1607 PetscErrorCode ierr; 1608 PetscInt n,m = A->rmap->n,i; 1609 const PetscInt *idx,*diag; 1610 1611 PetscFunctionBegin; 1612 its = its*lits; 1613 1614 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1615 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1616 a->fshift = fshift; 1617 a->omega = omega; 1618 1619 diag = a->diag; 1620 t = a->ssor_work; 1621 idiag = a->idiag; 1622 mdiag = a->mdiag; 1623 1624 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1625 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1626 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1627 if (flag == SOR_APPLY_UPPER) { 1628 /* apply (U + D/omega) to the vector */ 1629 bs = b; 1630 for (i=0; i<m; i++) { 1631 d = fshift + mdiag[i]; 1632 n = a->i[i+1] - diag[i] - 1; 1633 idx = a->j + diag[i] + 1; 1634 v = a->a + diag[i] + 1; 1635 sum = b[i]*d/omega; 1636 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1637 x[i] = sum; 1638 } 1639 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1640 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1641 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1642 PetscFunctionReturn(0); 1643 } 1644 1645 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1646 else if (flag & SOR_EISENSTAT) { 1647 /* Let A = L + U + D; where L is lower trianglar, 1648 U is upper triangular, E = D/omega; This routine applies 1649 1650 (L + E)^{-1} A (U + E)^{-1} 1651 1652 to a vector efficiently using Eisenstat's trick. 1653 */ 1654 scale = (2.0/omega) - 1.0; 1655 1656 /* x = (E + U)^{-1} b */ 1657 for (i=m-1; i>=0; i--) { 1658 n = a->i[i+1] - diag[i] - 1; 1659 idx = a->j + diag[i] + 1; 1660 v = a->a + diag[i] + 1; 1661 sum = b[i]; 1662 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1663 x[i] = sum*idiag[i]; 1664 } 1665 1666 /* t = b - (2*E - D)x */ 1667 v = a->a; 1668 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1669 1670 /* t = (E + L)^{-1}t */ 1671 ts = t; 1672 diag = a->diag; 1673 for (i=0; i<m; i++) { 1674 n = diag[i] - a->i[i]; 1675 idx = a->j + a->i[i]; 1676 v = a->a + a->i[i]; 1677 sum = t[i]; 1678 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1679 t[i] = sum*idiag[i]; 1680 /* x = x + t */ 1681 x[i] += t[i]; 1682 } 1683 1684 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1685 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1686 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1687 PetscFunctionReturn(0); 1688 } 1689 if (flag & SOR_ZERO_INITIAL_GUESS) { 1690 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1691 for (i=0; i<m; i++) { 1692 n = diag[i] - a->i[i]; 1693 idx = a->j + a->i[i]; 1694 v = a->a + a->i[i]; 1695 sum = b[i]; 1696 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1697 t[i] = sum; 1698 x[i] = sum*idiag[i]; 1699 } 1700 xb = t; 1701 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1702 } else xb = b; 1703 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1704 for (i=m-1; i>=0; i--) { 1705 n = a->i[i+1] - diag[i] - 1; 1706 idx = a->j + diag[i] + 1; 1707 v = a->a + diag[i] + 1; 1708 sum = xb[i]; 1709 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1710 if (xb == b) { 1711 x[i] = sum*idiag[i]; 1712 } else { 1713 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1714 } 1715 } 1716 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1717 } 1718 its--; 1719 } 1720 while (its--) { 1721 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1722 for (i=0; i<m; i++) { 1723 /* lower */ 1724 n = diag[i] - a->i[i]; 1725 idx = a->j + a->i[i]; 1726 v = a->a + a->i[i]; 1727 sum = b[i]; 1728 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1729 t[i] = sum; /* save application of the lower-triangular part */ 1730 /* upper */ 1731 n = a->i[i+1] - diag[i] - 1; 1732 idx = a->j + diag[i] + 1; 1733 v = a->a + diag[i] + 1; 1734 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1735 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1736 } 1737 xb = t; 1738 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1739 } else xb = b; 1740 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1741 for (i=m-1; i>=0; i--) { 1742 sum = xb[i]; 1743 if (xb == b) { 1744 /* whole matrix (no checkpointing available) */ 1745 n = a->i[i+1] - a->i[i]; 1746 idx = a->j + a->i[i]; 1747 v = a->a + a->i[i]; 1748 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1749 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1750 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1751 n = a->i[i+1] - diag[i] - 1; 1752 idx = a->j + diag[i] + 1; 1753 v = a->a + diag[i] + 1; 1754 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1755 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1756 } 1757 } 1758 if (xb == b) { 1759 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1760 } else { 1761 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1762 } 1763 } 1764 } 1765 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1766 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1767 PetscFunctionReturn(0); 1768 } 1769 1770 1771 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1772 { 1773 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1774 1775 PetscFunctionBegin; 1776 info->block_size = 1.0; 1777 info->nz_allocated = (double)a->maxnz; 1778 info->nz_used = (double)a->nz; 1779 info->nz_unneeded = (double)(a->maxnz - a->nz); 1780 info->assemblies = (double)A->num_ass; 1781 info->mallocs = (double)A->info.mallocs; 1782 info->memory = ((PetscObject)A)->mem; 1783 if (A->factortype) { 1784 info->fill_ratio_given = A->info.fill_ratio_given; 1785 info->fill_ratio_needed = A->info.fill_ratio_needed; 1786 info->factor_mallocs = A->info.factor_mallocs; 1787 } else { 1788 info->fill_ratio_given = 0; 1789 info->fill_ratio_needed = 0; 1790 info->factor_mallocs = 0; 1791 } 1792 PetscFunctionReturn(0); 1793 } 1794 1795 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1796 { 1797 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1798 PetscInt i,m = A->rmap->n - 1; 1799 PetscErrorCode ierr; 1800 const PetscScalar *xx; 1801 PetscScalar *bb; 1802 PetscInt d = 0; 1803 1804 PetscFunctionBegin; 1805 if (x && b) { 1806 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1807 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1808 for (i=0; i<N; i++) { 1809 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1810 bb[rows[i]] = diag*xx[rows[i]]; 1811 } 1812 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1813 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1814 } 1815 1816 if (a->keepnonzeropattern) { 1817 for (i=0; i<N; i++) { 1818 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1819 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1820 } 1821 if (diag != 0.0) { 1822 for (i=0; i<N; i++) { 1823 d = rows[i]; 1824 if (a->diag[d] >= a->i[d+1]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in the zeroed row %D",d); 1825 } 1826 for (i=0; i<N; i++) { 1827 a->a[a->diag[rows[i]]] = diag; 1828 } 1829 } 1830 } else { 1831 if (diag != 0.0) { 1832 for (i=0; i<N; i++) { 1833 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1834 if (a->ilen[rows[i]] > 0) { 1835 a->ilen[rows[i]] = 1; 1836 a->a[a->i[rows[i]]] = diag; 1837 a->j[a->i[rows[i]]] = rows[i]; 1838 } else { /* in case row was completely empty */ 1839 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1840 } 1841 } 1842 } else { 1843 for (i=0; i<N; i++) { 1844 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1845 a->ilen[rows[i]] = 0; 1846 } 1847 } 1848 A->nonzerostate++; 1849 } 1850 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1851 PetscFunctionReturn(0); 1852 } 1853 1854 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1855 { 1856 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1857 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1858 PetscErrorCode ierr; 1859 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1860 const PetscScalar *xx; 1861 PetscScalar *bb; 1862 1863 PetscFunctionBegin; 1864 if (x && b) { 1865 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1866 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1867 vecs = PETSC_TRUE; 1868 } 1869 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 1870 for (i=0; i<N; i++) { 1871 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1872 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1873 1874 zeroed[rows[i]] = PETSC_TRUE; 1875 } 1876 for (i=0; i<A->rmap->n; i++) { 1877 if (!zeroed[i]) { 1878 for (j=a->i[i]; j<a->i[i+1]; j++) { 1879 if (zeroed[a->j[j]]) { 1880 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1881 a->a[j] = 0.0; 1882 } 1883 } 1884 } else if (vecs) bb[i] = diag*xx[i]; 1885 } 1886 if (x && b) { 1887 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1888 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1889 } 1890 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1891 if (diag != 0.0) { 1892 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1893 if (missing) { 1894 if (a->nonew) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1895 else { 1896 for (i=0; i<N; i++) { 1897 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1898 } 1899 } 1900 } else { 1901 for (i=0; i<N; i++) { 1902 a->a[a->diag[rows[i]]] = diag; 1903 } 1904 } 1905 } 1906 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1907 PetscFunctionReturn(0); 1908 } 1909 1910 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1911 { 1912 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1913 PetscInt *itmp; 1914 1915 PetscFunctionBegin; 1916 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1917 1918 *nz = a->i[row+1] - a->i[row]; 1919 if (v) *v = a->a + a->i[row]; 1920 if (idx) { 1921 itmp = a->j + a->i[row]; 1922 if (*nz) *idx = itmp; 1923 else *idx = 0; 1924 } 1925 PetscFunctionReturn(0); 1926 } 1927 1928 /* remove this function? */ 1929 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1930 { 1931 PetscFunctionBegin; 1932 PetscFunctionReturn(0); 1933 } 1934 1935 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1936 { 1937 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1938 MatScalar *v = a->a; 1939 PetscReal sum = 0.0; 1940 PetscErrorCode ierr; 1941 PetscInt i,j; 1942 1943 PetscFunctionBegin; 1944 if (type == NORM_FROBENIUS) { 1945 #if defined(PETSC_USE_REAL___FP16) 1946 PetscBLASInt one = 1,nz = a->nz; 1947 *nrm = BLASnrm2_(&nz,v,&one); 1948 #else 1949 for (i=0; i<a->nz; i++) { 1950 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1951 } 1952 *nrm = PetscSqrtReal(sum); 1953 #endif 1954 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 1955 } else if (type == NORM_1) { 1956 PetscReal *tmp; 1957 PetscInt *jj = a->j; 1958 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 1959 *nrm = 0.0; 1960 for (j=0; j<a->nz; j++) { 1961 tmp[*jj++] += PetscAbsScalar(*v); v++; 1962 } 1963 for (j=0; j<A->cmap->n; j++) { 1964 if (tmp[j] > *nrm) *nrm = tmp[j]; 1965 } 1966 ierr = PetscFree(tmp);CHKERRQ(ierr); 1967 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1968 } else if (type == NORM_INFINITY) { 1969 *nrm = 0.0; 1970 for (j=0; j<A->rmap->n; j++) { 1971 v = a->a + a->i[j]; 1972 sum = 0.0; 1973 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1974 sum += PetscAbsScalar(*v); v++; 1975 } 1976 if (sum > *nrm) *nrm = sum; 1977 } 1978 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1979 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1980 PetscFunctionReturn(0); 1981 } 1982 1983 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 1984 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 1985 { 1986 PetscErrorCode ierr; 1987 PetscInt i,j,anzj; 1988 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 1989 PetscInt an=A->cmap->N,am=A->rmap->N; 1990 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 1991 1992 PetscFunctionBegin; 1993 /* Allocate space for symbolic transpose info and work array */ 1994 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 1995 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 1996 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 1997 1998 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 1999 /* Note: offset by 1 for fast conversion into csr format. */ 2000 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2001 /* Form ati for csr format of A^T. */ 2002 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2003 2004 /* Copy ati into atfill so we have locations of the next free space in atj */ 2005 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2006 2007 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2008 for (i=0;i<am;i++) { 2009 anzj = ai[i+1] - ai[i]; 2010 for (j=0;j<anzj;j++) { 2011 atj[atfill[*aj]] = i; 2012 atfill[*aj++] += 1; 2013 } 2014 } 2015 2016 /* Clean up temporary space and complete requests. */ 2017 ierr = PetscFree(atfill);CHKERRQ(ierr); 2018 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2019 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2020 2021 b = (Mat_SeqAIJ*)((*B)->data); 2022 b->free_a = PETSC_FALSE; 2023 b->free_ij = PETSC_TRUE; 2024 b->nonew = 0; 2025 PetscFunctionReturn(0); 2026 } 2027 2028 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2029 { 2030 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2031 Mat C; 2032 PetscErrorCode ierr; 2033 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2034 MatScalar *array = a->a; 2035 2036 PetscFunctionBegin; 2037 if (reuse == MAT_INPLACE_MATRIX && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2038 2039 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 2040 ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); 2041 2042 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2043 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2044 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2045 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2046 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2047 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2048 ierr = PetscFree(col);CHKERRQ(ierr); 2049 } else { 2050 C = *B; 2051 } 2052 2053 for (i=0; i<m; i++) { 2054 len = ai[i+1]-ai[i]; 2055 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2056 array += len; 2057 aj += len; 2058 } 2059 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2060 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2061 2062 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 2063 *B = C; 2064 } else { 2065 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 2066 } 2067 PetscFunctionReturn(0); 2068 } 2069 2070 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2071 { 2072 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2073 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2074 MatScalar *va,*vb; 2075 PetscErrorCode ierr; 2076 PetscInt ma,na,mb,nb, i; 2077 2078 PetscFunctionBegin; 2079 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2080 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2081 if (ma!=nb || na!=mb) { 2082 *f = PETSC_FALSE; 2083 PetscFunctionReturn(0); 2084 } 2085 aii = aij->i; bii = bij->i; 2086 adx = aij->j; bdx = bij->j; 2087 va = aij->a; vb = bij->a; 2088 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2089 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2090 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2091 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2092 2093 *f = PETSC_TRUE; 2094 for (i=0; i<ma; i++) { 2095 while (aptr[i]<aii[i+1]) { 2096 PetscInt idc,idr; 2097 PetscScalar vc,vr; 2098 /* column/row index/value */ 2099 idc = adx[aptr[i]]; 2100 idr = bdx[bptr[idc]]; 2101 vc = va[aptr[i]]; 2102 vr = vb[bptr[idc]]; 2103 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2104 *f = PETSC_FALSE; 2105 goto done; 2106 } else { 2107 aptr[i]++; 2108 if (B || i!=idc) bptr[idc]++; 2109 } 2110 } 2111 } 2112 done: 2113 ierr = PetscFree(aptr);CHKERRQ(ierr); 2114 ierr = PetscFree(bptr);CHKERRQ(ierr); 2115 PetscFunctionReturn(0); 2116 } 2117 2118 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2119 { 2120 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2121 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2122 MatScalar *va,*vb; 2123 PetscErrorCode ierr; 2124 PetscInt ma,na,mb,nb, i; 2125 2126 PetscFunctionBegin; 2127 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2128 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2129 if (ma!=nb || na!=mb) { 2130 *f = PETSC_FALSE; 2131 PetscFunctionReturn(0); 2132 } 2133 aii = aij->i; bii = bij->i; 2134 adx = aij->j; bdx = bij->j; 2135 va = aij->a; vb = bij->a; 2136 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2137 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2138 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2139 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2140 2141 *f = PETSC_TRUE; 2142 for (i=0; i<ma; i++) { 2143 while (aptr[i]<aii[i+1]) { 2144 PetscInt idc,idr; 2145 PetscScalar vc,vr; 2146 /* column/row index/value */ 2147 idc = adx[aptr[i]]; 2148 idr = bdx[bptr[idc]]; 2149 vc = va[aptr[i]]; 2150 vr = vb[bptr[idc]]; 2151 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2152 *f = PETSC_FALSE; 2153 goto done; 2154 } else { 2155 aptr[i]++; 2156 if (B || i!=idc) bptr[idc]++; 2157 } 2158 } 2159 } 2160 done: 2161 ierr = PetscFree(aptr);CHKERRQ(ierr); 2162 ierr = PetscFree(bptr);CHKERRQ(ierr); 2163 PetscFunctionReturn(0); 2164 } 2165 2166 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2167 { 2168 PetscErrorCode ierr; 2169 2170 PetscFunctionBegin; 2171 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2172 PetscFunctionReturn(0); 2173 } 2174 2175 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2176 { 2177 PetscErrorCode ierr; 2178 2179 PetscFunctionBegin; 2180 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2181 PetscFunctionReturn(0); 2182 } 2183 2184 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2185 { 2186 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2187 const PetscScalar *l,*r; 2188 PetscScalar x; 2189 MatScalar *v; 2190 PetscErrorCode ierr; 2191 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2192 const PetscInt *jj; 2193 2194 PetscFunctionBegin; 2195 if (ll) { 2196 /* The local size is used so that VecMPI can be passed to this routine 2197 by MatDiagonalScale_MPIAIJ */ 2198 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2199 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2200 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2201 v = a->a; 2202 for (i=0; i<m; i++) { 2203 x = l[i]; 2204 M = a->i[i+1] - a->i[i]; 2205 for (j=0; j<M; j++) (*v++) *= x; 2206 } 2207 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2208 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2209 } 2210 if (rr) { 2211 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2212 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2213 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2214 v = a->a; jj = a->j; 2215 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2216 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2217 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2218 } 2219 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2220 PetscFunctionReturn(0); 2221 } 2222 2223 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2224 { 2225 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2226 PetscErrorCode ierr; 2227 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2228 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2229 const PetscInt *irow,*icol; 2230 PetscInt nrows,ncols; 2231 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2232 MatScalar *a_new,*mat_a; 2233 Mat C; 2234 PetscBool stride; 2235 2236 PetscFunctionBegin; 2237 2238 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2239 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2240 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2241 2242 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2243 if (stride) { 2244 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2245 } else { 2246 first = 0; 2247 step = 0; 2248 } 2249 if (stride && step == 1) { 2250 /* special case of contiguous rows */ 2251 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2252 /* loop over new rows determining lens and starting points */ 2253 for (i=0; i<nrows; i++) { 2254 kstart = ai[irow[i]]; 2255 kend = kstart + ailen[irow[i]]; 2256 starts[i] = kstart; 2257 for (k=kstart; k<kend; k++) { 2258 if (aj[k] >= first) { 2259 starts[i] = k; 2260 break; 2261 } 2262 } 2263 sum = 0; 2264 while (k < kend) { 2265 if (aj[k++] >= first+ncols) break; 2266 sum++; 2267 } 2268 lens[i] = sum; 2269 } 2270 /* create submatrix */ 2271 if (scall == MAT_REUSE_MATRIX) { 2272 PetscInt n_cols,n_rows; 2273 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2274 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2275 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2276 C = *B; 2277 } else { 2278 PetscInt rbs,cbs; 2279 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2280 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2281 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2282 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2283 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2284 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2285 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2286 } 2287 c = (Mat_SeqAIJ*)C->data; 2288 2289 /* loop over rows inserting into submatrix */ 2290 a_new = c->a; 2291 j_new = c->j; 2292 i_new = c->i; 2293 2294 for (i=0; i<nrows; i++) { 2295 ii = starts[i]; 2296 lensi = lens[i]; 2297 for (k=0; k<lensi; k++) { 2298 *j_new++ = aj[ii+k] - first; 2299 } 2300 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2301 a_new += lensi; 2302 i_new[i+1] = i_new[i] + lensi; 2303 c->ilen[i] = lensi; 2304 } 2305 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2306 } else { 2307 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2308 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2309 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2310 for (i=0; i<ncols; i++) { 2311 #if defined(PETSC_USE_DEBUG) 2312 if (icol[i] >= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); 2313 #endif 2314 smap[icol[i]] = i+1; 2315 } 2316 2317 /* determine lens of each row */ 2318 for (i=0; i<nrows; i++) { 2319 kstart = ai[irow[i]]; 2320 kend = kstart + a->ilen[irow[i]]; 2321 lens[i] = 0; 2322 for (k=kstart; k<kend; k++) { 2323 if (smap[aj[k]]) { 2324 lens[i]++; 2325 } 2326 } 2327 } 2328 /* Create and fill new matrix */ 2329 if (scall == MAT_REUSE_MATRIX) { 2330 PetscBool equal; 2331 2332 c = (Mat_SeqAIJ*)((*B)->data); 2333 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2334 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2335 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2336 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2337 C = *B; 2338 } else { 2339 PetscInt rbs,cbs; 2340 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2341 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2342 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2343 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2344 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2345 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2346 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2347 } 2348 c = (Mat_SeqAIJ*)(C->data); 2349 for (i=0; i<nrows; i++) { 2350 row = irow[i]; 2351 kstart = ai[row]; 2352 kend = kstart + a->ilen[row]; 2353 mat_i = c->i[i]; 2354 mat_j = c->j + mat_i; 2355 mat_a = c->a + mat_i; 2356 mat_ilen = c->ilen + i; 2357 for (k=kstart; k<kend; k++) { 2358 if ((tcol=smap[a->j[k]])) { 2359 *mat_j++ = tcol - 1; 2360 *mat_a++ = a->a[k]; 2361 (*mat_ilen)++; 2362 2363 } 2364 } 2365 } 2366 /* Free work space */ 2367 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2368 ierr = PetscFree(smap);CHKERRQ(ierr); 2369 ierr = PetscFree(lens);CHKERRQ(ierr); 2370 /* sort */ 2371 for (i = 0; i < nrows; i++) { 2372 PetscInt ilen; 2373 2374 mat_i = c->i[i]; 2375 mat_j = c->j + mat_i; 2376 mat_a = c->a + mat_i; 2377 ilen = c->ilen[i]; 2378 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2379 } 2380 } 2381 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2382 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2383 2384 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2385 *B = C; 2386 PetscFunctionReturn(0); 2387 } 2388 2389 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2390 { 2391 PetscErrorCode ierr; 2392 Mat B; 2393 2394 PetscFunctionBegin; 2395 if (scall == MAT_INITIAL_MATRIX) { 2396 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2397 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2398 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2399 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2400 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2401 *subMat = B; 2402 } else { 2403 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2404 } 2405 PetscFunctionReturn(0); 2406 } 2407 2408 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2409 { 2410 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2411 PetscErrorCode ierr; 2412 Mat outA; 2413 PetscBool row_identity,col_identity; 2414 2415 PetscFunctionBegin; 2416 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2417 2418 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2419 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2420 2421 outA = inA; 2422 outA->factortype = MAT_FACTOR_LU; 2423 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2424 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2425 2426 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2427 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2428 2429 a->row = row; 2430 2431 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2432 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2433 2434 a->col = col; 2435 2436 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2437 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2438 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2439 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2440 2441 if (!a->solve_work) { /* this matrix may have been factored before */ 2442 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2443 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2444 } 2445 2446 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2447 if (row_identity && col_identity) { 2448 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2449 } else { 2450 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2451 } 2452 PetscFunctionReturn(0); 2453 } 2454 2455 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2456 { 2457 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2458 PetscScalar oalpha = alpha; 2459 PetscErrorCode ierr; 2460 PetscBLASInt one = 1,bnz; 2461 2462 PetscFunctionBegin; 2463 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2464 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2465 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2466 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2467 PetscFunctionReturn(0); 2468 } 2469 2470 PetscErrorCode MatDestroySubMatrices_Private(Mat_SubSppt *submatj) 2471 { 2472 PetscErrorCode ierr; 2473 PetscInt i; 2474 2475 PetscFunctionBegin; 2476 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2477 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2478 2479 for (i=0; i<submatj->nrqr; ++i) { 2480 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2481 } 2482 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2483 2484 if (submatj->rbuf1) { 2485 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2486 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2487 } 2488 2489 for (i=0; i<submatj->nrqs; ++i) { 2490 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2491 } 2492 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2493 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2494 } 2495 2496 #if defined(PETSC_USE_CTABLE) 2497 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2498 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2499 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2500 #else 2501 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2502 #endif 2503 2504 if (!submatj->allcolumns) { 2505 #if defined(PETSC_USE_CTABLE) 2506 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2507 #else 2508 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2509 #endif 2510 } 2511 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2512 2513 ierr = PetscFree(submatj);CHKERRQ(ierr); 2514 PetscFunctionReturn(0); 2515 } 2516 2517 PetscErrorCode MatDestroy_SeqAIJ_Submatrices(Mat C) 2518 { 2519 PetscErrorCode ierr; 2520 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2521 Mat_SubSppt *submatj = c->submatis1; 2522 2523 PetscFunctionBegin; 2524 printf("MatDestroy_SeqAIJ_Submatrices...\n"); 2525 ierr = submatj->destroy(C);CHKERRQ(ierr); 2526 ierr = MatDestroySubMatrices_Private(submatj);CHKERRQ(ierr); 2527 PetscFunctionReturn(0); 2528 } 2529 2530 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2531 { 2532 PetscErrorCode ierr; 2533 PetscInt i; 2534 2535 PetscFunctionBegin; 2536 /* Destroy dummy submatrices (*mat)[n]...(*mat)[n+nstages-1] used for reuse struct Mat_SubSppt */ 2537 if ((*mat)[n]) { 2538 PetscBool isdummy; 2539 ierr = PetscObjectTypeCompare((PetscObject)(*mat)[n],MATDUMMY,&isdummy);CHKERRQ(ierr); 2540 if (isdummy) { 2541 Mat_SubSppt* smat = (Mat_SubSppt*)((*mat)[n]->data); /* singleis and nstages are saved in (*mat)[n]->data */ 2542 printf("isdummy ...\n"); 2543 if (smat && !smat->singleis) { 2544 PetscInt i,nstages=smat->nstages; 2545 for (i=0; i<nstages; i++) { 2546 ierr = MatDestroy(&(*mat)[n+i]);CHKERRQ(ierr); 2547 } 2548 } 2549 } 2550 } 2551 2552 for (i=0; i<n; i++) { 2553 Mat C=(*mat)[i]; 2554 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2555 Mat_SubSppt *submatj = c->submatis1; 2556 2557 if (submatj) { 2558 ierr = submatj->destroy(C);CHKERRQ(ierr); 2559 ierr = MatDestroySubMatrices_Private(submatj);CHKERRQ(ierr); 2560 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2561 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2562 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2563 } else { 2564 ierr = MatDestroy(&C);CHKERRQ(ierr); 2565 } 2566 } 2567 ierr = PetscFree(*mat);CHKERRQ(ierr); 2568 PetscFunctionReturn(0); 2569 } 2570 2571 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2572 { 2573 PetscErrorCode ierr; 2574 PetscInt i; 2575 2576 PetscFunctionBegin; 2577 if (scall == MAT_INITIAL_MATRIX) { 2578 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2579 } 2580 2581 for (i=0; i<n; i++) { 2582 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2583 } 2584 PetscFunctionReturn(0); 2585 } 2586 2587 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2588 { 2589 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2590 PetscErrorCode ierr; 2591 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2592 const PetscInt *idx; 2593 PetscInt start,end,*ai,*aj; 2594 PetscBT table; 2595 2596 PetscFunctionBegin; 2597 m = A->rmap->n; 2598 ai = a->i; 2599 aj = a->j; 2600 2601 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2602 2603 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2604 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2605 2606 for (i=0; i<is_max; i++) { 2607 /* Initialize the two local arrays */ 2608 isz = 0; 2609 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2610 2611 /* Extract the indices, assume there can be duplicate entries */ 2612 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2613 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2614 2615 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2616 for (j=0; j<n; ++j) { 2617 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2618 } 2619 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2620 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2621 2622 k = 0; 2623 for (j=0; j<ov; j++) { /* for each overlap */ 2624 n = isz; 2625 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2626 row = nidx[k]; 2627 start = ai[row]; 2628 end = ai[row+1]; 2629 for (l = start; l<end; l++) { 2630 val = aj[l]; 2631 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2632 } 2633 } 2634 } 2635 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2636 } 2637 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2638 ierr = PetscFree(nidx);CHKERRQ(ierr); 2639 PetscFunctionReturn(0); 2640 } 2641 2642 /* -------------------------------------------------------------- */ 2643 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2644 { 2645 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2646 PetscErrorCode ierr; 2647 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2648 const PetscInt *row,*col; 2649 PetscInt *cnew,j,*lens; 2650 IS icolp,irowp; 2651 PetscInt *cwork = NULL; 2652 PetscScalar *vwork = NULL; 2653 2654 PetscFunctionBegin; 2655 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2656 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2657 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2658 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2659 2660 /* determine lengths of permuted rows */ 2661 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2662 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2663 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2664 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2665 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2666 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2667 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2668 ierr = PetscFree(lens);CHKERRQ(ierr); 2669 2670 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2671 for (i=0; i<m; i++) { 2672 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2673 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2674 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2675 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2676 } 2677 ierr = PetscFree(cnew);CHKERRQ(ierr); 2678 2679 (*B)->assembled = PETSC_FALSE; 2680 2681 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2682 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2683 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2684 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2685 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2686 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2687 PetscFunctionReturn(0); 2688 } 2689 2690 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2691 { 2692 PetscErrorCode ierr; 2693 2694 PetscFunctionBegin; 2695 /* If the two matrices have the same copy implementation, use fast copy. */ 2696 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2697 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2698 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2699 2700 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2701 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2702 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2703 } else { 2704 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2705 } 2706 PetscFunctionReturn(0); 2707 } 2708 2709 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2710 { 2711 PetscErrorCode ierr; 2712 2713 PetscFunctionBegin; 2714 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2715 PetscFunctionReturn(0); 2716 } 2717 2718 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2719 { 2720 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2721 2722 PetscFunctionBegin; 2723 *array = a->a; 2724 PetscFunctionReturn(0); 2725 } 2726 2727 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2728 { 2729 PetscFunctionBegin; 2730 PetscFunctionReturn(0); 2731 } 2732 2733 /* 2734 Computes the number of nonzeros per row needed for preallocation when X and Y 2735 have different nonzero structure. 2736 */ 2737 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2738 { 2739 PetscInt i,j,k,nzx,nzy; 2740 2741 PetscFunctionBegin; 2742 /* Set the number of nonzeros in the new matrix */ 2743 for (i=0; i<m; i++) { 2744 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2745 nzx = xi[i+1] - xi[i]; 2746 nzy = yi[i+1] - yi[i]; 2747 nnz[i] = 0; 2748 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2749 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2750 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2751 nnz[i]++; 2752 } 2753 for (; k<nzy; k++) nnz[i]++; 2754 } 2755 PetscFunctionReturn(0); 2756 } 2757 2758 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2759 { 2760 PetscInt m = Y->rmap->N; 2761 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2762 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2763 PetscErrorCode ierr; 2764 2765 PetscFunctionBegin; 2766 /* Set the number of nonzeros in the new matrix */ 2767 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2768 PetscFunctionReturn(0); 2769 } 2770 2771 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2772 { 2773 PetscErrorCode ierr; 2774 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2775 PetscBLASInt one=1,bnz; 2776 2777 PetscFunctionBegin; 2778 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2779 if (str == SAME_NONZERO_PATTERN) { 2780 PetscScalar alpha = a; 2781 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2782 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2783 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2784 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2785 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2786 } else { 2787 Mat B; 2788 PetscInt *nnz; 2789 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2790 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2791 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2792 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2793 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2794 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2795 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2796 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2797 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2798 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2799 ierr = PetscFree(nnz);CHKERRQ(ierr); 2800 } 2801 PetscFunctionReturn(0); 2802 } 2803 2804 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2805 { 2806 #if defined(PETSC_USE_COMPLEX) 2807 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2808 PetscInt i,nz; 2809 PetscScalar *a; 2810 2811 PetscFunctionBegin; 2812 nz = aij->nz; 2813 a = aij->a; 2814 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2815 #else 2816 PetscFunctionBegin; 2817 #endif 2818 PetscFunctionReturn(0); 2819 } 2820 2821 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2822 { 2823 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2824 PetscErrorCode ierr; 2825 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2826 PetscReal atmp; 2827 PetscScalar *x; 2828 MatScalar *aa; 2829 2830 PetscFunctionBegin; 2831 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2832 aa = a->a; 2833 ai = a->i; 2834 aj = a->j; 2835 2836 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2837 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2838 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2839 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2840 for (i=0; i<m; i++) { 2841 ncols = ai[1] - ai[0]; ai++; 2842 x[i] = 0.0; 2843 for (j=0; j<ncols; j++) { 2844 atmp = PetscAbsScalar(*aa); 2845 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2846 aa++; aj++; 2847 } 2848 } 2849 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2850 PetscFunctionReturn(0); 2851 } 2852 2853 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2854 { 2855 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2856 PetscErrorCode ierr; 2857 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2858 PetscScalar *x; 2859 MatScalar *aa; 2860 2861 PetscFunctionBegin; 2862 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2863 aa = a->a; 2864 ai = a->i; 2865 aj = a->j; 2866 2867 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2868 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2869 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2870 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2871 for (i=0; i<m; i++) { 2872 ncols = ai[1] - ai[0]; ai++; 2873 if (ncols == A->cmap->n) { /* row is dense */ 2874 x[i] = *aa; if (idx) idx[i] = 0; 2875 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2876 x[i] = 0.0; 2877 if (idx) { 2878 idx[i] = 0; /* in case ncols is zero */ 2879 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2880 if (aj[j] > j) { 2881 idx[i] = j; 2882 break; 2883 } 2884 } 2885 } 2886 } 2887 for (j=0; j<ncols; j++) { 2888 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2889 aa++; aj++; 2890 } 2891 } 2892 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2893 PetscFunctionReturn(0); 2894 } 2895 2896 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2897 { 2898 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2899 PetscErrorCode ierr; 2900 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2901 PetscReal atmp; 2902 PetscScalar *x; 2903 MatScalar *aa; 2904 2905 PetscFunctionBegin; 2906 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2907 aa = a->a; 2908 ai = a->i; 2909 aj = a->j; 2910 2911 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2912 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2913 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2914 if (n != A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector, %D vs. %D rows", A->rmap->n, n); 2915 for (i=0; i<m; i++) { 2916 ncols = ai[1] - ai[0]; ai++; 2917 if (ncols) { 2918 /* Get first nonzero */ 2919 for (j = 0; j < ncols; j++) { 2920 atmp = PetscAbsScalar(aa[j]); 2921 if (atmp > 1.0e-12) { 2922 x[i] = atmp; 2923 if (idx) idx[i] = aj[j]; 2924 break; 2925 } 2926 } 2927 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2928 } else { 2929 x[i] = 0.0; if (idx) idx[i] = 0; 2930 } 2931 for (j = 0; j < ncols; j++) { 2932 atmp = PetscAbsScalar(*aa); 2933 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2934 aa++; aj++; 2935 } 2936 } 2937 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2938 PetscFunctionReturn(0); 2939 } 2940 2941 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2942 { 2943 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2944 PetscErrorCode ierr; 2945 PetscInt i,j,m = A->rmap->n,ncols,n; 2946 const PetscInt *ai,*aj; 2947 PetscScalar *x; 2948 const MatScalar *aa; 2949 2950 PetscFunctionBegin; 2951 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2952 aa = a->a; 2953 ai = a->i; 2954 aj = a->j; 2955 2956 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2957 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2958 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2959 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2960 for (i=0; i<m; i++) { 2961 ncols = ai[1] - ai[0]; ai++; 2962 if (ncols == A->cmap->n) { /* row is dense */ 2963 x[i] = *aa; if (idx) idx[i] = 0; 2964 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2965 x[i] = 0.0; 2966 if (idx) { /* find first implicit 0.0 in the row */ 2967 idx[i] = 0; /* in case ncols is zero */ 2968 for (j=0; j<ncols; j++) { 2969 if (aj[j] > j) { 2970 idx[i] = j; 2971 break; 2972 } 2973 } 2974 } 2975 } 2976 for (j=0; j<ncols; j++) { 2977 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2978 aa++; aj++; 2979 } 2980 } 2981 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2982 PetscFunctionReturn(0); 2983 } 2984 2985 #include <petscblaslapack.h> 2986 #include <petsc/private/kernels/blockinvert.h> 2987 2988 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 2989 { 2990 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 2991 PetscErrorCode ierr; 2992 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 2993 MatScalar *diag,work[25],*v_work; 2994 PetscReal shift = 0.0; 2995 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 2996 2997 PetscFunctionBegin; 2998 allowzeropivot = PetscNot(A->erroriffailure); 2999 if (a->ibdiagvalid) { 3000 if (values) *values = a->ibdiag; 3001 PetscFunctionReturn(0); 3002 } 3003 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3004 if (!a->ibdiag) { 3005 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3006 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3007 } 3008 diag = a->ibdiag; 3009 if (values) *values = a->ibdiag; 3010 /* factor and invert each block */ 3011 switch (bs) { 3012 case 1: 3013 for (i=0; i<mbs; i++) { 3014 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3015 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3016 if (allowzeropivot) { 3017 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3018 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3019 A->factorerror_zeropivot_row = i; 3020 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3021 } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot %g tolerance %g",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON); 3022 } 3023 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3024 } 3025 break; 3026 case 2: 3027 for (i=0; i<mbs; i++) { 3028 ij[0] = 2*i; ij[1] = 2*i + 1; 3029 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3030 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3031 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3032 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3033 diag += 4; 3034 } 3035 break; 3036 case 3: 3037 for (i=0; i<mbs; i++) { 3038 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3039 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3040 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3041 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3042 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3043 diag += 9; 3044 } 3045 break; 3046 case 4: 3047 for (i=0; i<mbs; i++) { 3048 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3049 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3050 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3051 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3052 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3053 diag += 16; 3054 } 3055 break; 3056 case 5: 3057 for (i=0; i<mbs; i++) { 3058 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3059 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3060 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3061 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3062 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3063 diag += 25; 3064 } 3065 break; 3066 case 6: 3067 for (i=0; i<mbs; i++) { 3068 ij[0] = 6*i; ij[1] = 6*i + 1; ij[2] = 6*i + 2; ij[3] = 6*i + 3; ij[4] = 6*i + 4; ij[5] = 6*i + 5; 3069 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3070 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3071 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3072 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3073 diag += 36; 3074 } 3075 break; 3076 case 7: 3077 for (i=0; i<mbs; i++) { 3078 ij[0] = 7*i; ij[1] = 7*i + 1; ij[2] = 7*i + 2; ij[3] = 7*i + 3; ij[4] = 7*i + 4; ij[5] = 7*i + 5; ij[5] = 7*i + 6; 3079 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3080 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3081 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3082 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3083 diag += 49; 3084 } 3085 break; 3086 default: 3087 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3088 for (i=0; i<mbs; i++) { 3089 for (j=0; j<bs; j++) { 3090 IJ[j] = bs*i + j; 3091 } 3092 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3093 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3094 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3095 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3096 diag += bs2; 3097 } 3098 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3099 } 3100 a->ibdiagvalid = PETSC_TRUE; 3101 PetscFunctionReturn(0); 3102 } 3103 3104 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3105 { 3106 PetscErrorCode ierr; 3107 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3108 PetscScalar a; 3109 PetscInt m,n,i,j,col; 3110 3111 PetscFunctionBegin; 3112 if (!x->assembled) { 3113 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3114 for (i=0; i<m; i++) { 3115 for (j=0; j<aij->imax[i]; j++) { 3116 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3117 col = (PetscInt)(n*PetscRealPart(a)); 3118 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3119 } 3120 } 3121 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3122 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3123 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3124 PetscFunctionReturn(0); 3125 } 3126 3127 PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) 3128 { 3129 PetscErrorCode ierr; 3130 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; 3131 3132 PetscFunctionBegin; 3133 if (!Y->preallocated || !aij->nz) { 3134 ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); 3135 } 3136 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 3137 PetscFunctionReturn(0); 3138 } 3139 3140 /* -------------------------------------------------------------------*/ 3141 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3142 MatGetRow_SeqAIJ, 3143 MatRestoreRow_SeqAIJ, 3144 MatMult_SeqAIJ, 3145 /* 4*/ MatMultAdd_SeqAIJ, 3146 MatMultTranspose_SeqAIJ, 3147 MatMultTransposeAdd_SeqAIJ, 3148 0, 3149 0, 3150 0, 3151 /* 10*/ 0, 3152 MatLUFactor_SeqAIJ, 3153 0, 3154 MatSOR_SeqAIJ, 3155 MatTranspose_SeqAIJ, 3156 /*1 5*/ MatGetInfo_SeqAIJ, 3157 MatEqual_SeqAIJ, 3158 MatGetDiagonal_SeqAIJ, 3159 MatDiagonalScale_SeqAIJ, 3160 MatNorm_SeqAIJ, 3161 /* 20*/ 0, 3162 MatAssemblyEnd_SeqAIJ, 3163 MatSetOption_SeqAIJ, 3164 MatZeroEntries_SeqAIJ, 3165 /* 24*/ MatZeroRows_SeqAIJ, 3166 0, 3167 0, 3168 0, 3169 0, 3170 /* 29*/ MatSetUp_SeqAIJ, 3171 0, 3172 0, 3173 0, 3174 0, 3175 /* 34*/ MatDuplicate_SeqAIJ, 3176 0, 3177 0, 3178 MatILUFactor_SeqAIJ, 3179 0, 3180 /* 39*/ MatAXPY_SeqAIJ, 3181 MatCreateSubMatrices_SeqAIJ, 3182 MatIncreaseOverlap_SeqAIJ, 3183 MatGetValues_SeqAIJ, 3184 MatCopy_SeqAIJ, 3185 /* 44*/ MatGetRowMax_SeqAIJ, 3186 MatScale_SeqAIJ, 3187 MatShift_SeqAIJ, 3188 MatDiagonalSet_SeqAIJ, 3189 MatZeroRowsColumns_SeqAIJ, 3190 /* 49*/ MatSetRandom_SeqAIJ, 3191 MatGetRowIJ_SeqAIJ, 3192 MatRestoreRowIJ_SeqAIJ, 3193 MatGetColumnIJ_SeqAIJ, 3194 MatRestoreColumnIJ_SeqAIJ, 3195 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3196 0, 3197 0, 3198 MatPermute_SeqAIJ, 3199 0, 3200 /* 59*/ 0, 3201 MatDestroy_SeqAIJ, 3202 MatView_SeqAIJ, 3203 0, 3204 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3205 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3206 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3207 0, 3208 0, 3209 0, 3210 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3211 MatGetRowMinAbs_SeqAIJ, 3212 0, 3213 0, 3214 0, 3215 /* 74*/ 0, 3216 MatFDColoringApply_AIJ, 3217 0, 3218 0, 3219 0, 3220 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3221 0, 3222 0, 3223 0, 3224 MatLoad_SeqAIJ, 3225 /* 84*/ MatIsSymmetric_SeqAIJ, 3226 MatIsHermitian_SeqAIJ, 3227 0, 3228 0, 3229 0, 3230 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3231 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3232 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3233 MatPtAP_SeqAIJ_SeqAIJ, 3234 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3235 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3236 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3237 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3238 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3239 0, 3240 /* 99*/ 0, 3241 0, 3242 0, 3243 MatConjugate_SeqAIJ, 3244 0, 3245 /*104*/ MatSetValuesRow_SeqAIJ, 3246 MatRealPart_SeqAIJ, 3247 MatImaginaryPart_SeqAIJ, 3248 0, 3249 0, 3250 /*109*/ MatMatSolve_SeqAIJ, 3251 0, 3252 MatGetRowMin_SeqAIJ, 3253 0, 3254 MatMissingDiagonal_SeqAIJ, 3255 /*114*/ 0, 3256 0, 3257 0, 3258 0, 3259 0, 3260 /*119*/ 0, 3261 0, 3262 0, 3263 0, 3264 MatGetMultiProcBlock_SeqAIJ, 3265 /*124*/ MatFindNonzeroRows_SeqAIJ, 3266 MatGetColumnNorms_SeqAIJ, 3267 MatInvertBlockDiagonal_SeqAIJ, 3268 0, 3269 0, 3270 /*129*/ 0, 3271 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3272 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3273 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3274 MatTransposeColoringCreate_SeqAIJ, 3275 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3276 MatTransColoringApplyDenToSp_SeqAIJ, 3277 MatRARt_SeqAIJ_SeqAIJ, 3278 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3279 MatRARtNumeric_SeqAIJ_SeqAIJ, 3280 /*139*/0, 3281 0, 3282 0, 3283 MatFDColoringSetUp_SeqXAIJ, 3284 MatFindOffBlockDiagonalEntries_SeqAIJ, 3285 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3286 MatDestroySubMatrices_SeqAIJ 3287 }; 3288 3289 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3290 { 3291 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3292 PetscInt i,nz,n; 3293 3294 PetscFunctionBegin; 3295 nz = aij->maxnz; 3296 n = mat->rmap->n; 3297 for (i=0; i<nz; i++) { 3298 aij->j[i] = indices[i]; 3299 } 3300 aij->nz = nz; 3301 for (i=0; i<n; i++) { 3302 aij->ilen[i] = aij->imax[i]; 3303 } 3304 PetscFunctionReturn(0); 3305 } 3306 3307 /*@ 3308 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3309 in the matrix. 3310 3311 Input Parameters: 3312 + mat - the SeqAIJ matrix 3313 - indices - the column indices 3314 3315 Level: advanced 3316 3317 Notes: 3318 This can be called if you have precomputed the nonzero structure of the 3319 matrix and want to provide it to the matrix object to improve the performance 3320 of the MatSetValues() operation. 3321 3322 You MUST have set the correct numbers of nonzeros per row in the call to 3323 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3324 3325 MUST be called before any calls to MatSetValues(); 3326 3327 The indices should start with zero, not one. 3328 3329 @*/ 3330 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3331 { 3332 PetscErrorCode ierr; 3333 3334 PetscFunctionBegin; 3335 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3336 PetscValidPointer(indices,2); 3337 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3338 PetscFunctionReturn(0); 3339 } 3340 3341 /* ----------------------------------------------------------------------------------------*/ 3342 3343 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3344 { 3345 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3346 PetscErrorCode ierr; 3347 size_t nz = aij->i[mat->rmap->n]; 3348 3349 PetscFunctionBegin; 3350 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3351 3352 /* allocate space for values if not already there */ 3353 if (!aij->saved_values) { 3354 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3355 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3356 } 3357 3358 /* copy values over */ 3359 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3360 PetscFunctionReturn(0); 3361 } 3362 3363 /*@ 3364 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3365 example, reuse of the linear part of a Jacobian, while recomputing the 3366 nonlinear portion. 3367 3368 Collect on Mat 3369 3370 Input Parameters: 3371 . mat - the matrix (currently only AIJ matrices support this option) 3372 3373 Level: advanced 3374 3375 Common Usage, with SNESSolve(): 3376 $ Create Jacobian matrix 3377 $ Set linear terms into matrix 3378 $ Apply boundary conditions to matrix, at this time matrix must have 3379 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3380 $ boundary conditions again will not change the nonzero structure 3381 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3382 $ ierr = MatStoreValues(mat); 3383 $ Call SNESSetJacobian() with matrix 3384 $ In your Jacobian routine 3385 $ ierr = MatRetrieveValues(mat); 3386 $ Set nonlinear terms in matrix 3387 3388 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3389 $ // build linear portion of Jacobian 3390 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3391 $ ierr = MatStoreValues(mat); 3392 $ loop over nonlinear iterations 3393 $ ierr = MatRetrieveValues(mat); 3394 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3395 $ // call MatAssemblyBegin/End() on matrix 3396 $ Solve linear system with Jacobian 3397 $ endloop 3398 3399 Notes: 3400 Matrix must already be assemblied before calling this routine 3401 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3402 calling this routine. 3403 3404 When this is called multiple times it overwrites the previous set of stored values 3405 and does not allocated additional space. 3406 3407 .seealso: MatRetrieveValues() 3408 3409 @*/ 3410 PetscErrorCode MatStoreValues(Mat mat) 3411 { 3412 PetscErrorCode ierr; 3413 3414 PetscFunctionBegin; 3415 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3416 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3417 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3418 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3419 PetscFunctionReturn(0); 3420 } 3421 3422 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3423 { 3424 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3425 PetscErrorCode ierr; 3426 PetscInt nz = aij->i[mat->rmap->n]; 3427 3428 PetscFunctionBegin; 3429 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3430 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3431 /* copy values over */ 3432 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3433 PetscFunctionReturn(0); 3434 } 3435 3436 /*@ 3437 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3438 example, reuse of the linear part of a Jacobian, while recomputing the 3439 nonlinear portion. 3440 3441 Collect on Mat 3442 3443 Input Parameters: 3444 . mat - the matrix (currently only AIJ matrices support this option) 3445 3446 Level: advanced 3447 3448 .seealso: MatStoreValues() 3449 3450 @*/ 3451 PetscErrorCode MatRetrieveValues(Mat mat) 3452 { 3453 PetscErrorCode ierr; 3454 3455 PetscFunctionBegin; 3456 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3457 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3458 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3459 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3460 PetscFunctionReturn(0); 3461 } 3462 3463 3464 /* --------------------------------------------------------------------------------*/ 3465 /*@C 3466 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3467 (the default parallel PETSc format). For good matrix assembly performance 3468 the user should preallocate the matrix storage by setting the parameter nz 3469 (or the array nnz). By setting these parameters accurately, performance 3470 during matrix assembly can be increased by more than a factor of 50. 3471 3472 Collective on MPI_Comm 3473 3474 Input Parameters: 3475 + comm - MPI communicator, set to PETSC_COMM_SELF 3476 . m - number of rows 3477 . n - number of columns 3478 . nz - number of nonzeros per row (same for all rows) 3479 - nnz - array containing the number of nonzeros in the various rows 3480 (possibly different for each row) or NULL 3481 3482 Output Parameter: 3483 . A - the matrix 3484 3485 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3486 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3487 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3488 3489 Notes: 3490 If nnz is given then nz is ignored 3491 3492 The AIJ format (also called the Yale sparse matrix format or 3493 compressed row storage), is fully compatible with standard Fortran 77 3494 storage. That is, the stored row and column indices can begin at 3495 either one (as in Fortran) or zero. See the users' manual for details. 3496 3497 Specify the preallocated storage with either nz or nnz (not both). 3498 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3499 allocation. For large problems you MUST preallocate memory or you 3500 will get TERRIBLE performance, see the users' manual chapter on matrices. 3501 3502 By default, this format uses inodes (identical nodes) when possible, to 3503 improve numerical efficiency of matrix-vector products and solves. We 3504 search for consecutive rows with the same nonzero structure, thereby 3505 reusing matrix information to achieve increased efficiency. 3506 3507 Options Database Keys: 3508 + -mat_no_inode - Do not use inodes 3509 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3510 3511 Level: intermediate 3512 3513 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3514 3515 @*/ 3516 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3517 { 3518 PetscErrorCode ierr; 3519 3520 PetscFunctionBegin; 3521 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3522 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3523 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3524 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3525 PetscFunctionReturn(0); 3526 } 3527 3528 /*@C 3529 MatSeqAIJSetPreallocation - For good matrix assembly performance 3530 the user should preallocate the matrix storage by setting the parameter nz 3531 (or the array nnz). By setting these parameters accurately, performance 3532 during matrix assembly can be increased by more than a factor of 50. 3533 3534 Collective on MPI_Comm 3535 3536 Input Parameters: 3537 + B - The matrix 3538 . nz - number of nonzeros per row (same for all rows) 3539 - nnz - array containing the number of nonzeros in the various rows 3540 (possibly different for each row) or NULL 3541 3542 Notes: 3543 If nnz is given then nz is ignored 3544 3545 The AIJ format (also called the Yale sparse matrix format or 3546 compressed row storage), is fully compatible with standard Fortran 77 3547 storage. That is, the stored row and column indices can begin at 3548 either one (as in Fortran) or zero. See the users' manual for details. 3549 3550 Specify the preallocated storage with either nz or nnz (not both). 3551 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3552 allocation. For large problems you MUST preallocate memory or you 3553 will get TERRIBLE performance, see the users' manual chapter on matrices. 3554 3555 You can call MatGetInfo() to get information on how effective the preallocation was; 3556 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3557 You can also run with the option -info and look for messages with the string 3558 malloc in them to see if additional memory allocation was needed. 3559 3560 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3561 entries or columns indices 3562 3563 By default, this format uses inodes (identical nodes) when possible, to 3564 improve numerical efficiency of matrix-vector products and solves. We 3565 search for consecutive rows with the same nonzero structure, thereby 3566 reusing matrix information to achieve increased efficiency. 3567 3568 Options Database Keys: 3569 + -mat_no_inode - Do not use inodes 3570 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3571 - -mat_aij_oneindex - Internally use indexing starting at 1 3572 rather than 0. Note that when calling MatSetValues(), 3573 the user still MUST index entries starting at 0! 3574 3575 Level: intermediate 3576 3577 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3578 3579 @*/ 3580 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3581 { 3582 PetscErrorCode ierr; 3583 3584 PetscFunctionBegin; 3585 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3586 PetscValidType(B,1); 3587 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3588 PetscFunctionReturn(0); 3589 } 3590 3591 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3592 { 3593 Mat_SeqAIJ *b; 3594 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3595 PetscErrorCode ierr; 3596 PetscInt i; 3597 3598 PetscFunctionBegin; 3599 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3600 if (nz == MAT_SKIP_ALLOCATION) { 3601 skipallocation = PETSC_TRUE; 3602 nz = 0; 3603 } 3604 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3605 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3606 3607 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3608 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3609 if (nnz) { 3610 for (i=0; i<B->rmap->n; i++) { 3611 if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 3612 if (nnz[i] > B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than row length: local row %D value %d rowlength %D",i,nnz[i],B->cmap->n); 3613 } 3614 } 3615 3616 B->preallocated = PETSC_TRUE; 3617 3618 b = (Mat_SeqAIJ*)B->data; 3619 3620 if (!skipallocation) { 3621 if (!b->imax) { 3622 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3623 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3624 } 3625 if (!nnz) { 3626 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3627 else if (nz < 0) nz = 1; 3628 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3629 nz = nz*B->rmap->n; 3630 } else { 3631 nz = 0; 3632 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3633 } 3634 /* b->ilen will count nonzeros in each row so far. */ 3635 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3636 3637 /* allocate the matrix space */ 3638 /* FIXME: should B's old memory be unlogged? */ 3639 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3640 if (B->structure_only) { 3641 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3642 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3643 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3644 } else { 3645 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3646 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3647 } 3648 b->i[0] = 0; 3649 for (i=1; i<B->rmap->n+1; i++) { 3650 b->i[i] = b->i[i-1] + b->imax[i-1]; 3651 } 3652 if (B->structure_only) { 3653 b->singlemalloc = PETSC_FALSE; 3654 b->free_a = PETSC_FALSE; 3655 } else { 3656 b->singlemalloc = PETSC_TRUE; 3657 b->free_a = PETSC_TRUE; 3658 } 3659 b->free_ij = PETSC_TRUE; 3660 } else { 3661 b->free_a = PETSC_FALSE; 3662 b->free_ij = PETSC_FALSE; 3663 } 3664 3665 b->nz = 0; 3666 b->maxnz = nz; 3667 B->info.nz_unneeded = (double)b->maxnz; 3668 if (realalloc) { 3669 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3670 } 3671 B->was_assembled = PETSC_FALSE; 3672 B->assembled = PETSC_FALSE; 3673 PetscFunctionReturn(0); 3674 } 3675 3676 /*@ 3677 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3678 3679 Input Parameters: 3680 + B - the matrix 3681 . i - the indices into j for the start of each row (starts with zero) 3682 . j - the column indices for each row (starts with zero) these must be sorted for each row 3683 - v - optional values in the matrix 3684 3685 Level: developer 3686 3687 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3688 3689 .keywords: matrix, aij, compressed row, sparse, sequential 3690 3691 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3692 @*/ 3693 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3694 { 3695 PetscErrorCode ierr; 3696 3697 PetscFunctionBegin; 3698 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3699 PetscValidType(B,1); 3700 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3701 PetscFunctionReturn(0); 3702 } 3703 3704 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3705 { 3706 PetscInt i; 3707 PetscInt m,n; 3708 PetscInt nz; 3709 PetscInt *nnz, nz_max = 0; 3710 PetscScalar *values; 3711 PetscErrorCode ierr; 3712 3713 PetscFunctionBegin; 3714 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3715 3716 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3717 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3718 3719 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3720 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3721 for (i = 0; i < m; i++) { 3722 nz = Ii[i+1]- Ii[i]; 3723 nz_max = PetscMax(nz_max, nz); 3724 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3725 nnz[i] = nz; 3726 } 3727 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3728 ierr = PetscFree(nnz);CHKERRQ(ierr); 3729 3730 if (v) { 3731 values = (PetscScalar*) v; 3732 } else { 3733 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3734 } 3735 3736 for (i = 0; i < m; i++) { 3737 nz = Ii[i+1] - Ii[i]; 3738 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3739 } 3740 3741 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3742 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3743 3744 if (!v) { 3745 ierr = PetscFree(values);CHKERRQ(ierr); 3746 } 3747 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3748 PetscFunctionReturn(0); 3749 } 3750 3751 #include <../src/mat/impls/dense/seq/dense.h> 3752 #include <petsc/private/kernels/petscaxpy.h> 3753 3754 /* 3755 Computes (B'*A')' since computing B*A directly is untenable 3756 3757 n p p 3758 ( ) ( ) ( ) 3759 m ( A ) * n ( B ) = m ( C ) 3760 ( ) ( ) ( ) 3761 3762 */ 3763 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3764 { 3765 PetscErrorCode ierr; 3766 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3767 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3768 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3769 PetscInt i,n,m,q,p; 3770 const PetscInt *ii,*idx; 3771 const PetscScalar *b,*a,*a_q; 3772 PetscScalar *c,*c_q; 3773 3774 PetscFunctionBegin; 3775 m = A->rmap->n; 3776 n = A->cmap->n; 3777 p = B->cmap->n; 3778 a = sub_a->v; 3779 b = sub_b->a; 3780 c = sub_c->v; 3781 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3782 3783 ii = sub_b->i; 3784 idx = sub_b->j; 3785 for (i=0; i<n; i++) { 3786 q = ii[i+1] - ii[i]; 3787 while (q-->0) { 3788 c_q = c + m*(*idx); 3789 a_q = a + m*i; 3790 PetscKernelAXPY(c_q,*b,a_q,m); 3791 idx++; 3792 b++; 3793 } 3794 } 3795 PetscFunctionReturn(0); 3796 } 3797 3798 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3799 { 3800 PetscErrorCode ierr; 3801 PetscInt m=A->rmap->n,n=B->cmap->n; 3802 Mat Cmat; 3803 3804 PetscFunctionBegin; 3805 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %D != B->rmap->n %D\n",A->cmap->n,B->rmap->n); 3806 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3807 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3808 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3809 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3810 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3811 3812 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3813 3814 *C = Cmat; 3815 PetscFunctionReturn(0); 3816 } 3817 3818 /* ----------------------------------------------------------------*/ 3819 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3820 { 3821 PetscErrorCode ierr; 3822 3823 PetscFunctionBegin; 3824 if (scall == MAT_INITIAL_MATRIX) { 3825 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3826 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3827 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3828 } 3829 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3830 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3831 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3832 PetscFunctionReturn(0); 3833 } 3834 3835 3836 /*MC 3837 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3838 based on compressed sparse row format. 3839 3840 Options Database Keys: 3841 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3842 3843 Level: beginner 3844 3845 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3846 M*/ 3847 3848 /*MC 3849 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3850 3851 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3852 and MATMPIAIJ otherwise. As a result, for single process communicators, 3853 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3854 for communicators controlling multiple processes. It is recommended that you call both of 3855 the above preallocation routines for simplicity. 3856 3857 Options Database Keys: 3858 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3859 3860 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3861 enough exist. 3862 3863 Level: beginner 3864 3865 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3866 M*/ 3867 3868 /*MC 3869 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3870 3871 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3872 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3873 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3874 for communicators controlling multiple processes. It is recommended that you call both of 3875 the above preallocation routines for simplicity. 3876 3877 Options Database Keys: 3878 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3879 3880 Level: beginner 3881 3882 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3883 M*/ 3884 3885 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3886 #if defined(PETSC_HAVE_ELEMENTAL) 3887 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 3888 #endif 3889 #if defined(PETSC_HAVE_HYPRE) 3890 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 3891 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 3892 #endif 3893 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 3894 3895 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3896 PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3897 PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3898 #endif 3899 3900 3901 /*@C 3902 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 3903 3904 Not Collective 3905 3906 Input Parameter: 3907 . mat - a MATSEQAIJ matrix 3908 3909 Output Parameter: 3910 . array - pointer to the data 3911 3912 Level: intermediate 3913 3914 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3915 @*/ 3916 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3917 { 3918 PetscErrorCode ierr; 3919 3920 PetscFunctionBegin; 3921 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3922 PetscFunctionReturn(0); 3923 } 3924 3925 /*@C 3926 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3927 3928 Not Collective 3929 3930 Input Parameter: 3931 . mat - a MATSEQAIJ matrix 3932 3933 Output Parameter: 3934 . nz - the maximum number of nonzeros in any row 3935 3936 Level: intermediate 3937 3938 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3939 @*/ 3940 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3941 { 3942 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3943 3944 PetscFunctionBegin; 3945 *nz = aij->rmax; 3946 PetscFunctionReturn(0); 3947 } 3948 3949 /*@C 3950 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3951 3952 Not Collective 3953 3954 Input Parameters: 3955 . mat - a MATSEQAIJ matrix 3956 . array - pointer to the data 3957 3958 Level: intermediate 3959 3960 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3961 @*/ 3962 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3963 { 3964 PetscErrorCode ierr; 3965 3966 PetscFunctionBegin; 3967 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3968 PetscFunctionReturn(0); 3969 } 3970 3971 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3972 { 3973 Mat_SeqAIJ *b; 3974 PetscErrorCode ierr; 3975 PetscMPIInt size; 3976 3977 PetscFunctionBegin; 3978 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3979 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3980 3981 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3982 3983 B->data = (void*)b; 3984 3985 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3986 3987 b->row = 0; 3988 b->col = 0; 3989 b->icol = 0; 3990 b->reallocs = 0; 3991 b->ignorezeroentries = PETSC_FALSE; 3992 b->roworiented = PETSC_TRUE; 3993 b->nonew = 0; 3994 b->diag = 0; 3995 b->solve_work = 0; 3996 B->spptr = 0; 3997 b->saved_values = 0; 3998 b->idiag = 0; 3999 b->mdiag = 0; 4000 b->ssor_work = 0; 4001 b->omega = 1.0; 4002 b->fshift = 0.0; 4003 b->idiagvalid = PETSC_FALSE; 4004 b->ibdiagvalid = PETSC_FALSE; 4005 b->keepnonzeropattern = PETSC_FALSE; 4006 4007 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4008 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4009 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4010 4011 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4012 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4013 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4014 #endif 4015 4016 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4017 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4018 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4019 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4020 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4021 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4022 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4023 #if defined(PETSC_HAVE_ELEMENTAL) 4024 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4025 #endif 4026 #if defined(PETSC_HAVE_HYPRE) 4027 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4028 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4029 #endif 4030 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4031 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4032 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4033 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4034 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4035 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4036 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4037 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4038 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4039 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4040 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4041 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4042 PetscFunctionReturn(0); 4043 } 4044 4045 /* 4046 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4047 */ 4048 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4049 { 4050 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4051 PetscErrorCode ierr; 4052 PetscInt i,m = A->rmap->n; 4053 4054 PetscFunctionBegin; 4055 c = (Mat_SeqAIJ*)C->data; 4056 4057 C->factortype = A->factortype; 4058 c->row = 0; 4059 c->col = 0; 4060 c->icol = 0; 4061 c->reallocs = 0; 4062 4063 C->assembled = PETSC_TRUE; 4064 4065 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4066 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4067 4068 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4069 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4070 for (i=0; i<m; i++) { 4071 c->imax[i] = a->imax[i]; 4072 c->ilen[i] = a->ilen[i]; 4073 } 4074 4075 /* allocate the matrix space */ 4076 if (mallocmatspace) { 4077 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4078 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4079 4080 c->singlemalloc = PETSC_TRUE; 4081 4082 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4083 if (m > 0) { 4084 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4085 if (cpvalues == MAT_COPY_VALUES) { 4086 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4087 } else { 4088 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4089 } 4090 } 4091 } 4092 4093 c->ignorezeroentries = a->ignorezeroentries; 4094 c->roworiented = a->roworiented; 4095 c->nonew = a->nonew; 4096 if (a->diag) { 4097 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4098 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4099 for (i=0; i<m; i++) { 4100 c->diag[i] = a->diag[i]; 4101 } 4102 } else c->diag = 0; 4103 4104 c->solve_work = 0; 4105 c->saved_values = 0; 4106 c->idiag = 0; 4107 c->ssor_work = 0; 4108 c->keepnonzeropattern = a->keepnonzeropattern; 4109 c->free_a = PETSC_TRUE; 4110 c->free_ij = PETSC_TRUE; 4111 4112 c->rmax = a->rmax; 4113 c->nz = a->nz; 4114 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4115 C->preallocated = PETSC_TRUE; 4116 4117 c->compressedrow.use = a->compressedrow.use; 4118 c->compressedrow.nrows = a->compressedrow.nrows; 4119 if (a->compressedrow.use) { 4120 i = a->compressedrow.nrows; 4121 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4122 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4123 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4124 } else { 4125 c->compressedrow.use = PETSC_FALSE; 4126 c->compressedrow.i = NULL; 4127 c->compressedrow.rindex = NULL; 4128 } 4129 c->nonzerorowcnt = a->nonzerorowcnt; 4130 C->nonzerostate = A->nonzerostate; 4131 4132 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4133 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4134 PetscFunctionReturn(0); 4135 } 4136 4137 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4138 { 4139 PetscErrorCode ierr; 4140 4141 PetscFunctionBegin; 4142 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4143 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4144 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4145 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4146 } 4147 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4148 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4149 PetscFunctionReturn(0); 4150 } 4151 4152 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4153 { 4154 Mat_SeqAIJ *a; 4155 PetscErrorCode ierr; 4156 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4157 int fd; 4158 PetscMPIInt size; 4159 MPI_Comm comm; 4160 PetscInt bs = newMat->rmap->bs; 4161 4162 PetscFunctionBegin; 4163 /* force binary viewer to load .info file if it has not yet done so */ 4164 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4165 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4166 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4167 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4168 4169 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4170 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4171 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4172 if (bs < 0) bs = 1; 4173 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4174 4175 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4176 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4177 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4178 M = header[1]; N = header[2]; nz = header[3]; 4179 4180 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4181 4182 /* read in row lengths */ 4183 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4184 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4185 4186 /* check if sum of rowlengths is same as nz */ 4187 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4188 if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_READ,"Inconsistant matrix data in file. no-nonzeros = %dD, sum-row-lengths = %D\n",nz,sum); 4189 4190 /* set global size if not set already*/ 4191 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4192 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4193 } else { 4194 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4195 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4196 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4197 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4198 } 4199 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols); 4200 } 4201 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4202 a = (Mat_SeqAIJ*)newMat->data; 4203 4204 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4205 4206 /* read in nonzero values */ 4207 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4208 4209 /* set matrix "i" values */ 4210 a->i[0] = 0; 4211 for (i=1; i<= M; i++) { 4212 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4213 a->ilen[i-1] = rowlengths[i-1]; 4214 } 4215 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4216 4217 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4218 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4219 PetscFunctionReturn(0); 4220 } 4221 4222 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4223 { 4224 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4225 PetscErrorCode ierr; 4226 #if defined(PETSC_USE_COMPLEX) 4227 PetscInt k; 4228 #endif 4229 4230 PetscFunctionBegin; 4231 /* If the matrix dimensions are not equal,or no of nonzeros */ 4232 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4233 *flg = PETSC_FALSE; 4234 PetscFunctionReturn(0); 4235 } 4236 4237 /* if the a->i are the same */ 4238 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4239 if (!*flg) PetscFunctionReturn(0); 4240 4241 /* if a->j are the same */ 4242 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4243 if (!*flg) PetscFunctionReturn(0); 4244 4245 /* if a->a are the same */ 4246 #if defined(PETSC_USE_COMPLEX) 4247 for (k=0; k<a->nz; k++) { 4248 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4249 *flg = PETSC_FALSE; 4250 PetscFunctionReturn(0); 4251 } 4252 } 4253 #else 4254 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4255 #endif 4256 PetscFunctionReturn(0); 4257 } 4258 4259 /*@ 4260 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4261 provided by the user. 4262 4263 Collective on MPI_Comm 4264 4265 Input Parameters: 4266 + comm - must be an MPI communicator of size 1 4267 . m - number of rows 4268 . n - number of columns 4269 . i - row indices 4270 . j - column indices 4271 - a - matrix values 4272 4273 Output Parameter: 4274 . mat - the matrix 4275 4276 Level: intermediate 4277 4278 Notes: 4279 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4280 once the matrix is destroyed and not before 4281 4282 You cannot set new nonzero locations into this matrix, that will generate an error. 4283 4284 The i and j indices are 0 based 4285 4286 The format which is used for the sparse matrix input, is equivalent to a 4287 row-major ordering.. i.e for the following matrix, the input data expected is 4288 as shown 4289 4290 $ 1 0 0 4291 $ 2 0 3 4292 $ 4 5 6 4293 $ 4294 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4295 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4296 $ v = {1,2,3,4,5,6} [size = 6] 4297 4298 4299 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4300 4301 @*/ 4302 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4303 { 4304 PetscErrorCode ierr; 4305 PetscInt ii; 4306 Mat_SeqAIJ *aij; 4307 #if defined(PETSC_USE_DEBUG) 4308 PetscInt jj; 4309 #endif 4310 4311 PetscFunctionBegin; 4312 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4313 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4314 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4315 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4316 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4317 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4318 aij = (Mat_SeqAIJ*)(*mat)->data; 4319 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4320 4321 aij->i = i; 4322 aij->j = j; 4323 aij->a = a; 4324 aij->singlemalloc = PETSC_FALSE; 4325 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4326 aij->free_a = PETSC_FALSE; 4327 aij->free_ij = PETSC_FALSE; 4328 4329 for (ii=0; ii<m; ii++) { 4330 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4331 #if defined(PETSC_USE_DEBUG) 4332 if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %D length = %D",ii,i[ii+1] - i[ii]); 4333 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4334 if (j[jj] < j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual colum %D) in row %D is not sorted",jj-i[ii],j[jj],ii); 4335 if (j[jj] == j[jj]-1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual colum %D) in row %D is identical to previous entry",jj-i[ii],j[jj],ii); 4336 } 4337 #endif 4338 } 4339 #if defined(PETSC_USE_DEBUG) 4340 for (ii=0; ii<aij->i[m]; ii++) { 4341 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4342 if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %D index = %D",ii,j[ii]); 4343 } 4344 #endif 4345 4346 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4347 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4348 PetscFunctionReturn(0); 4349 } 4350 /*@C 4351 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4352 provided by the user. 4353 4354 Collective on MPI_Comm 4355 4356 Input Parameters: 4357 + comm - must be an MPI communicator of size 1 4358 . m - number of rows 4359 . n - number of columns 4360 . i - row indices 4361 . j - column indices 4362 . a - matrix values 4363 . nz - number of nonzeros 4364 - idx - 0 or 1 based 4365 4366 Output Parameter: 4367 . mat - the matrix 4368 4369 Level: intermediate 4370 4371 Notes: 4372 The i and j indices are 0 based 4373 4374 The format which is used for the sparse matrix input, is equivalent to a 4375 row-major ordering.. i.e for the following matrix, the input data expected is 4376 as shown: 4377 4378 1 0 0 4379 2 0 3 4380 4 5 6 4381 4382 i = {0,1,1,2,2,2} 4383 j = {0,0,2,0,1,2} 4384 v = {1,2,3,4,5,6} 4385 4386 4387 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4388 4389 @*/ 4390 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4391 { 4392 PetscErrorCode ierr; 4393 PetscInt ii, *nnz, one = 1,row,col; 4394 4395 4396 PetscFunctionBegin; 4397 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4398 for (ii = 0; ii < nz; ii++) { 4399 nnz[i[ii] - !!idx] += 1; 4400 } 4401 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4402 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4403 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4404 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4405 for (ii = 0; ii < nz; ii++) { 4406 if (idx) { 4407 row = i[ii] - 1; 4408 col = j[ii] - 1; 4409 } else { 4410 row = i[ii]; 4411 col = j[ii]; 4412 } 4413 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4414 } 4415 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4416 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4417 ierr = PetscFree(nnz);CHKERRQ(ierr); 4418 PetscFunctionReturn(0); 4419 } 4420 4421 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4422 { 4423 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4424 PetscErrorCode ierr; 4425 4426 PetscFunctionBegin; 4427 a->idiagvalid = PETSC_FALSE; 4428 a->ibdiagvalid = PETSC_FALSE; 4429 4430 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4431 PetscFunctionReturn(0); 4432 } 4433 4434 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4435 { 4436 PetscErrorCode ierr; 4437 PetscMPIInt size; 4438 4439 PetscFunctionBegin; 4440 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4441 if (size == 1) { 4442 if (scall == MAT_INITIAL_MATRIX) { 4443 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4444 } else { 4445 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4446 } 4447 } else { 4448 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4449 } 4450 PetscFunctionReturn(0); 4451 } 4452 4453 /* 4454 Permute A into C's *local* index space using rowemb,colemb. 4455 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4456 of [0,m), colemb is in [0,n). 4457 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4458 */ 4459 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4460 { 4461 /* If making this function public, change the error returned in this function away from _PLIB. */ 4462 PetscErrorCode ierr; 4463 Mat_SeqAIJ *Baij; 4464 PetscBool seqaij; 4465 PetscInt m,n,*nz,i,j,count; 4466 PetscScalar v; 4467 const PetscInt *rowindices,*colindices; 4468 4469 PetscFunctionBegin; 4470 if (!B) PetscFunctionReturn(0); 4471 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4472 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4473 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4474 if (rowemb) { 4475 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4476 if (m != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Row IS of size %D is incompatible with matrix row size %D",m,B->rmap->n); 4477 } else { 4478 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4479 } 4480 if (colemb) { 4481 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4482 if (n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Diag col IS of size %D is incompatible with input matrix col size %D",n,B->cmap->n); 4483 } else { 4484 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4485 } 4486 4487 Baij = (Mat_SeqAIJ*)(B->data); 4488 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4489 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4490 for (i=0; i<B->rmap->n; i++) { 4491 nz[i] = Baij->i[i+1] - Baij->i[i]; 4492 } 4493 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4494 ierr = PetscFree(nz);CHKERRQ(ierr); 4495 } 4496 if (pattern == SUBSET_NONZERO_PATTERN) { 4497 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4498 } 4499 count = 0; 4500 rowindices = NULL; 4501 colindices = NULL; 4502 if (rowemb) { 4503 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4504 } 4505 if (colemb) { 4506 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4507 } 4508 for (i=0; i<B->rmap->n; i++) { 4509 PetscInt row; 4510 row = i; 4511 if (rowindices) row = rowindices[i]; 4512 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4513 PetscInt col; 4514 col = Baij->j[count]; 4515 if (colindices) col = colindices[col]; 4516 v = Baij->a[count]; 4517 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4518 ++count; 4519 } 4520 } 4521 /* FIXME: set C's nonzerostate correctly. */ 4522 /* Assembly for C is necessary. */ 4523 C->preallocated = PETSC_TRUE; 4524 C->assembled = PETSC_TRUE; 4525 C->was_assembled = PETSC_FALSE; 4526 PetscFunctionReturn(0); 4527 } 4528 4529 PetscFunctionList MatSeqAIJList = NULL; 4530 4531 /*@C 4532 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4533 4534 Collective on Mat 4535 4536 Input Parameters: 4537 + mat - the matrix object 4538 - matype - matrix type 4539 4540 Options Database Key: 4541 . -mat_seqai_type <method> - for example seqaijcrl 4542 4543 4544 Level: intermediate 4545 4546 .keywords: Mat, MatType, set, method 4547 4548 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4549 @*/ 4550 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4551 { 4552 PetscErrorCode ierr,(*r)(Mat,const MatType,MatReuse,Mat*); 4553 PetscBool sametype; 4554 4555 PetscFunctionBegin; 4556 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4557 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4558 if (sametype) PetscFunctionReturn(0); 4559 4560 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4561 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4562 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4563 PetscFunctionReturn(0); 4564 } 4565 4566 4567 /*@C 4568 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4569 4570 Not Collective 4571 4572 Input Parameters: 4573 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4574 - function - routine to convert to subtype 4575 4576 Notes: 4577 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4578 4579 4580 Then, your matrix can be chosen with the procedural interface at runtime via the option 4581 $ -mat_seqaij_type my_mat 4582 4583 Level: advanced 4584 4585 .keywords: Mat, register 4586 4587 .seealso: MatSeqAIJRegisterAll() 4588 4589 4590 Level: advanced 4591 @*/ 4592 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,const MatType,MatReuse,Mat *)) 4593 { 4594 PetscErrorCode ierr; 4595 4596 PetscFunctionBegin; 4597 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4598 PetscFunctionReturn(0); 4599 } 4600 4601 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4602 4603 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,const MatType,MatReuse,Mat*); 4604 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,const MatType,MatReuse,Mat*); 4605 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4606 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat,const MatType,MatReuse,Mat*); 4607 #endif 4608 4609 /*@C 4610 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4611 4612 Not Collective 4613 4614 Level: advanced 4615 4616 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4617 4618 .keywords: KSP, register, all 4619 4620 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4621 @*/ 4622 PetscErrorCode MatSeqAIJRegisterAll(void) 4623 { 4624 PetscErrorCode ierr; 4625 4626 PetscFunctionBegin; 4627 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4628 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4629 4630 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4631 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4632 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4633 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4634 #endif 4635 PetscFunctionReturn(0); 4636 } 4637 4638 /* 4639 Special version for direct calls from Fortran 4640 */ 4641 #include <petsc/private/fortranimpl.h> 4642 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4643 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4644 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4645 #define matsetvaluesseqaij_ matsetvaluesseqaij 4646 #endif 4647 4648 /* Change these macros so can be used in void function */ 4649 #undef CHKERRQ 4650 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4651 #undef SETERRQ2 4652 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4653 #undef SETERRQ3 4654 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4655 4656 PETSC_EXTERN void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 4657 { 4658 Mat A = *AA; 4659 PetscInt m = *mm, n = *nn; 4660 InsertMode is = *isis; 4661 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4662 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4663 PetscInt *imax,*ai,*ailen; 4664 PetscErrorCode ierr; 4665 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4666 MatScalar *ap,value,*aa; 4667 PetscBool ignorezeroentries = a->ignorezeroentries; 4668 PetscBool roworiented = a->roworiented; 4669 4670 PetscFunctionBegin; 4671 MatCheckPreallocated(A,1); 4672 imax = a->imax; 4673 ai = a->i; 4674 ailen = a->ilen; 4675 aj = a->j; 4676 aa = a->a; 4677 4678 for (k=0; k<m; k++) { /* loop over added rows */ 4679 row = im[k]; 4680 if (row < 0) continue; 4681 #if defined(PETSC_USE_DEBUG) 4682 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4683 #endif 4684 rp = aj + ai[row]; ap = aa + ai[row]; 4685 rmax = imax[row]; nrow = ailen[row]; 4686 low = 0; 4687 high = nrow; 4688 for (l=0; l<n; l++) { /* loop over added columns */ 4689 if (in[l] < 0) continue; 4690 #if defined(PETSC_USE_DEBUG) 4691 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4692 #endif 4693 col = in[l]; 4694 if (roworiented) value = v[l + k*n]; 4695 else value = v[k + l*m]; 4696 4697 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4698 4699 if (col <= lastcol) low = 0; 4700 else high = nrow; 4701 lastcol = col; 4702 while (high-low > 5) { 4703 t = (low+high)/2; 4704 if (rp[t] > col) high = t; 4705 else low = t; 4706 } 4707 for (i=low; i<high; i++) { 4708 if (rp[i] > col) break; 4709 if (rp[i] == col) { 4710 if (is == ADD_VALUES) ap[i] += value; 4711 else ap[i] = value; 4712 goto noinsert; 4713 } 4714 } 4715 if (value == 0.0 && ignorezeroentries) goto noinsert; 4716 if (nonew == 1) goto noinsert; 4717 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4718 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4719 N = nrow++ - 1; a->nz++; high++; 4720 /* shift up all the later entries in this row */ 4721 for (ii=N; ii>=i; ii--) { 4722 rp[ii+1] = rp[ii]; 4723 ap[ii+1] = ap[ii]; 4724 } 4725 rp[i] = col; 4726 ap[i] = value; 4727 A->nonzerostate++; 4728 noinsert:; 4729 low = i + 1; 4730 } 4731 ailen[row] = nrow; 4732 } 4733 PetscFunctionReturnVoid(); 4734 } 4735 4736